ABSTRACT AN EVENT-ORIENTED CORN PRODUCTION SIMULATION MODEL By Samuel Dale Parsons A computer simulation model was developed for evalu- ating the physical performance of the corn production. harvesting and marketing system of an individual firm. The model was structured to provide the capability of evaluat- ing numerous user-specific variations in land base. equip- ment inventory. labor force, and management policy. The model developed utilizes: 1) a daily simulation technique for environmental and management factors associated with the system -- soil and crop attributes as well as operating procedures and labor availability may change from day to day: and 2) an event-oriented simulation technique for the performance of functional activities associated with the system -- tillage, planting, harvesting. crop or supply transport. and other activities. The development of this latter aspect of the model was based on a conceptualization of the corn production system as a set of mobile discrete objects (men. tractors. combines, trucks. etc.) that inter- act with a set of immobile discrete objects (fields. farm- stead facilities. off-farm markets, etc.) based on a set Samuel Dale Parsons of policy and procedure rules (some of which are Specified by the model-user) to accomplish the desired production. harvesting and marketing activities. The model consists of a very small main program and 130 subroutines that are called as needed. Of these, about #5 could be classified as input-output routines or those involved with the daily simulation aspect of the model. The remaining subroutines were required for the detailed activity-simulation, which utilized the filing system and event control features of the GASP II simulation language. Certain unique features of the model appear to be adequate, and necessary. for realistic performance results with complex multi-man, multi-machine corn production. harvesting and marketing systems. These include: 1) the definition of activity periods based on weather. soil. crop and/or management factors which permits the Specification, and determination of field operations and other activities that are feasible at any point in simulated time: and 2) the definition of a field-operations-status array, or similar accounting device, to facilitate scheduling and to maintain the current work/no-work status of fields that are to re- ceive various field operations. Another unique feature of the model. the provisions made for declaring an activity-simulation day on days when field work cannot be done, is also an important concept for realistic simulation results. In the real world non-field activities g9 occur on days when field work cannot be done Samuel Dale Parsons (equipment refueling and maintenance. corn handling, off- farm marketing. etc.) which permits a more efficient utili- zation of available field time on those days when it can be done. The model was developed sufficiently to demonstrate its use for a one-man system in which the corn shelled at ’harvest-time (with a self-propelled combine) is moved to on-farm high-moisture storage and/or to off-farm markets. To do so an example farm with four alternative equipment- management systems was devised. The daily simulation portion of the model and the event-oriented portion of the model performed in a reasonable and realistic manner for the single crop-year simulations. Certain features of the model developed are unique in comparison to other simulation models that have been deve- loped for crop production systems. For example, the capa- bility of simulating a series of several field Operations (and their necessary support functions) rather than just the so-called key operations (planting and/or harvesting). The capability of realistically evaluating the interaction of field equipment and/or transport subsystems and/or grain receiving facilities under specific operating policies and with specific physical constraints (field shapes, field arrangements, road networks. etc.) is another example. These capabilities, however, were not without certain ”costs”: complexity in specifying input information. Samuel Dale Parsons complexity in programming. especially for the activity- simulation. and relatively high computer storage and execu- tion time requirements. Because of these factors, the potential use of the model is probably not, as was initially hoped, as a management tool for practicing farm managers. Rather. its most important future role may be in deve- loping realistic performance coefficients for other simula- tion or optimization models -- particularly field efficiency values for equipment operating in specific situations. Another important use may be for sensitivity analysis, to determine what policies, procedures. characteristics or other factors significantly affect the performance of complex crop production systems. Such information could be used to establish criteria for developing simpler models for research and/or practical management purposes. Approved Major Professor Department Chairman AN EVENT-ORIENTED CORN PRODUCTION SIMULATION MODEL by Samuel Dale Parsons A THESIS submitted to lichigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Agricultural Engineering 1975 I; 4 t. \ ‘t ACKNOWLEDGEMENTS The author is indebted to many individuals for the successful completion of this thesis and his degree pro- gram. Those at Michigan State University include: Dr. J. B. Holtman for serving as his major professor: Dr. L. J. Connor. Dr. T. J. Manetsch. Dr. L. K. Pickett and Dr. C. J. Mackson for serving on his graduate committees R. G. White for assistance in gathering data and for continual encouragement: and Harvey Czerwinski and Rick Bergen for their assistance with subroutine testing and other computer- related activities. Those at Purdue University who deserve a special thanks include: B. A. McKenzie for his counsel and encour- agement. and J. L. Wheeler for technical assistance in the use of the computer OVERLAY technique. A very special thanks is given to the author's wife. Jane. and to his family for their patience. understanding and sacrifice during the entire course of this program. ii TABLE OF CONTENTS LIST OF TABLES . . . . e e . . . . e . . . LIST OF FIGURES. . . . e . e e . . e . e . INTRODUCTION 0 . e . . e . .‘. . . . . . . REVIEW OF LITERATURE . . . . . . . . Machinery Performance Measures. . . . Determining Machine Performance . . . Simulation Languages. 0 e e e. e e e e OBJECT IVES O O O O O O O O O O O O O O O O O O O O O SYSTEM BOUNDARIES AND DESIRED MODEL CHARACTERISTICS. MODEL INPUT CONSIDERATIONS O O O O O O O O O O Q 0 0 MODEL FORMULATION CONCEPTS AND MANAGEMENT POLICY OPTIONS O O O O O O O O O 0 Activity Period Concept . . . FIELD-OP-STATUS Array Concept Activity Class Concept. . . . Daily Simulation Concept. . . ACTIVITY-SIMULATION MODELING . . . . . . . Simulation with GASP. . . . File Organization for GASP Simulation. Attribute Organization and Management Non-Event Files . . . . .‘. . . . . of the. Event Control and Other Simulation Concepts . EVENTSCHEDULING.eeeeeeeeeece Activity State Flow Charts. . . . . . Computing Real Event Attribute Values DEMONSTRATED USE OF THE MODEL. . . . . . . Planting and Crop Development Results Activity Simulation Results . . . . . SUMMARY AND CONCLUSIONS. . . . . . . . . . RECOMMENDATIONS FOR FUTURE RESEARCH. . . . iii Page vi 1U 1h 17 19 23 21+ 27 TABLE OF CONTENTS (cont'd.) Page APPENDIX A: COMPUTER MODEL INPUT FORM . . . . . . . . 201 APPENDIX B: COMPOSITION OF THE NON-EVENT GASP FILES . 225 APPENDIX C. x-Y COORDINATE SYSTEM AND OTHER FIELD PROPERTIES. O O O O O O O O O I O O O O 232 APPENDIX D. ACTIVITY STATES PROPOSED FOR THE FILE 11 ENTITIES ASSOCIATED WITH ON-FARM DRYING. . . . . . . . . . . . . . . . . 237 APPENDIX E! COMPOSITION OF THE GASP EVENTS FILE FOR REAL EVENTS O O O O C O O I O I I O O I 238 REFERENCES 0 O O O O O O O O O O O O O O O O O O O O O 2’43 iv Table 1. 3. #. 5. 6. 7. 8. 9. 10. 11. 12. 13. LIST OF TABLES GASP Files Defined for Corn Production. Harvesting, and marketing Systems. . . . . Changes in GASP Filing Array Requirements with the Assembly of Equipment and Transport Sets in Files 7 and 8. . . . . . Activity States Defined for Equipment and Fleility Entities. s o s o o s o o s s o 0 Activity States Defined for Labor Entities . Repair Attribute Factors 0 s s s s e o s . 0 Real Events for A One-Nan Corn Harvesting and Handling System Without On-Farm Drying Travel Speeds for Various Mobile Entities. . Field Characteristics of the Example Farm. . Harvesting and marketing Alternatives Examined Planting and Crop Development for Example sthODSO s s s s o e o s o s o o s s s s 0 Summary of Activit Simulation Results (one'man Systems 0 s s s o s o o s s e s 0 Comparison of Activity-Simulation Days . . . Harvesting and Hauling Statistics for sthCl A s s s s o o s s s e s o s o 0.0 o Page 84 37 93 94 105 153 167 179 180 182 18“ 187 190 Figure 1. Overall Model Structure. . . . . . . . . . . . 2. Declaring An Activity-Simulation Day . . . . . 3. Concluding An Activity-Simulation Day. . . . . b. The GASP Filing Array. . . . . . . . . . . . . 5. Event Control with GASP. . . . . . . . . . . . 6. State Changes in Simulated Time. . . . . . . . 7. Scheduling of a Repair Activity. . . . . . . . 8. Event Control with Subroutine MYGASP . . . . . 9. Attributes of the Events File. . . . . . . . . 10. Executive Subroutine EXECl . . . . . . . . . . 11. Combine Unloading Patterns for STOP-Unloading. 12. Event Scheduling Sequence for Corn Harvesting and Handling Activities for A One-Man System Without On-Farm Drying . . . . . . . . . . . 13. Simple Activity State Flow Charts. . . . . . . 1h. Activity State Flow Chart for Grain Tank Unloading That Fills A Transport Set (One-Man System) . . . . . . . . . . . . . . 15. Sample Entity Positions and movements for . One-Man Harvesting Systems . . . . . . . . . 16. Alternate Travel Paths Between Two Points ' in Different Fields. . . . . . . . . . . . . 17. Sample Event Logs. . . . . . . . . . . . . . . 18. Physical Layout of Example Farm. . . . . . . . LIST OF FIGURES vi Page 47 59 65 73 80 92 107 110 113 119 130 11.7 1H9 152 155 16b 17# 178 LIST OF FIGURES (cont'do) Figure Page 19. Activity State-Time Information for System A Equipment. 0 e o o e o e e o o o e e o o e e e 189 Appendix Figure Bi. Files 2 through 5 —- Unassigned Field Equipment 0 e e e o o e o e o e o e o e e o o 225 B2. Files 6. 9 and 10 -- Labor. Field Operations and Fields "In-Process”. . . . . . 225 B3. File 7 -- Assembled Equipment Sets (Including Information Retained in F1138 2 and 4). o e e_o o e e e e c o o o o e 226 B4. File 8 -- Assembled Transport Sets (Including Information Retained in Files 2 and 5). o o o o o o o o o e o o e o e 226 B5. File 11 -- Farmstead Equipment and Structures, and Off-Farm Markets. . . . . . . 227 C1. Field Section PrOperties and Alternative ShaPGSo e o o e e e 0'. e e o o e e e e o o e 233 CZ. Partitioning A Field Into Smaller Sections. . . 235 E1. Real EventAttribute Requirements . . . . . . . 239 vii INTRODUCTION The operation of a commercial corn farm requires management skills and abilities unmatched in most other businesses. The corn producer must be a purchasing agent for production supplies, a salesman for the crop produced. and a host of other things. One of his key roles is to assemble and manage the system of men and machines needed to actually produce the crop (a biological product) in an environment that is usually unpredictable and sometimes hostile (the weather). Performing these functions-has become increasingly difficult as new technologies have continued to develop in all phases of corn production. Simply understanding the cause-effect relationships at work within a complex corn production system is not an easy task. The farm manager must be continually alert that some anticipated change in equipment, operating procedure or policy does not optimize or improve some component of the system at the expense of overall system performance. _ Computer simulation models have proven to be an effect- ive means of analyzing and understanding many complex systems. A carefully designed simulation model of the corn production system could be a practical management tool for the farm manager. as well as a powerful research tool for the agricultural scientist. How practical and how powerful this tool would be. though, depends on how well real world phenomena and processes can be modeled to produce realistic results. A f The development of such a model. in the author's judge- ment, should be done with two basic requirementsin minds 1) It should be highly user-specific. 1.9.. it should have the capability of dealing with a variety of real-world situations regarding the availability and use of land. equipment and labor. 2) It should employ event-oriented simulation techniques in order to produce the most realistic quantitative predic- tions of system performance possible. . The justification for these two requirements will be discussed in some detail. Each corn farm in existence today is unique in many ways. These include its location and physical makeup. and the farm manager's ability and biases regarding the adopt- ion of new technology. the operation of equipment. the use of part-time help. and so forth. The farm's very location defines certain factors which will affect the management and performance of a corn pro- duction system. The prevailing temperature and rainfall patterns in the area will influence such things as actual and potential yields. and the number of operating days possible in a given time period. The type. cost and avail- ability of part-time labor and custom services (for ferti- lizer and chemical application. harvesting. hauling. drying. etc.) will influence labor-equipment size relationships. The general farming pattern in the area (corn surplus vs. corn deficit areas). the type and distribution of roads in the area. and the number. size. type and distance to off-farm marketing outlets will influence such things as transport times for production supplies and marketed corn. the length of waiting lines at elevators during harvest. corn price.levels and moisture discount schedules. The physical makeup of the farm also affects system management and performance. The natural fertility and drainage of the soils will influence yield potential and equipment tractability. The soils' susceptibility to water and wind erosion will influence the advisability of fall tillage operations and may dictate row direction. The size and shape of fields will influence the field efficiency of equipment. and may dictate unload patterns for harvesting. and refill patterns for planting and other material appli- cation Jobs. The geographic distribution of fields. or of contiguous tracts of fields in the operation will influence travel and transport times. policies for the overnight stor- age of equipment (in-field versus at the farmstead). and the sequence in which fields receive a given field operation. The farm's total acreage. the size of the permanent labor force. the farm manager's use of part-time help in critical periods. and the complement of equipment in-place at any given time will all affect the management and per- formance of the over-all system. Equipment size is one characteristic that distinguishes the complement of machin- ery on one farm from that on another. The type of equip- ment. based on the particular practices the farm manager has selected to produce. harvest. and market the corn crop. is another distinguishing characteristic. The farm manager may also decide that certain practices should be done with custom-hired equipment. while others are performed with farm-controlled equipment. The corn production techniques of modern agriculture usually require equipment to perform all or most of the following field operations: residue management. tillage. planting. fertilizer application. special pest control pra- ctices (for weeds. insects. or corn diseases). harvesting. and transport of the harvested crop from the field. In addition. many corn producers also dry and/or store all or part of the crop on the farm where it is produced. This corn is then marketed off-farm. or through a complementary livestock enterprise on the farm. With each of these practices there is a multitude of alternative technologies which the farm manager may adopt. A few examples of alter- native technologies and their possible affect on system performance will be cited. In the area of tillage and planting systems. convent- ional tillage is still the most prevalent method of seedbed preparation used in most areas of the cornbelt. This method involves the use of a primary tillage tool (a moldboard or chisel plow used in the fall or spring). followed by one. two or more secondary tillage operations (with a disk. field cultivator. spring-tooth harrow. or similar implement in the spring) prior to planting. The primary tillage oper- ation may or may not be preceded with a residue management operation (disking or shredding of last year's cornstalks). It is now possible. however. to "prepare” the land and plant in as few as one or two trips over the field using so-called reduced tillage or no-till methods. Obviously the number and type of tillage operations to be performed. coupled with the total acreage to be planted and other factors. will influence the farm manager's equipment sizing. selection and scheduling policies. He may also have built- in constraints or biases (his own or imposed by the owner of rented land) which affect scheduling. For instance. he may want to perform a given field operation in various fields in a particular sequence. or certain fields will be fall plowed (weather and time permitting) while others will not because of the wind or water erosion hazard. Alternative technoldgies are also available for supply- ing the nutrient requirements (N. P’and K) of the crop. The farm manager'schoice of fertilizer materials and methods of application. as well as the required rates of application. can have an important influence on equipment sizing. select- ion and scheduling. and on system performance. Phosphorus (P) and potassium (K) may be bulk spread in a dry form prior to primary tillage or afterwards. This is usually done. however. (before the last secondary tillage operation preceding planting. They may also be applied. in either the liquid or dry form. and with nitrogen (N). as a sideband application of complete- mix starter fertilizer during planting. Bulk nitrogen is readily available in several forms. These include high-pressure gas (anhydrous ammonia). low- pressure liquids and non-pressure liquids. Application may be made in a variety of ways. The non-pressure materials can be surface applied with Special spraying equipment. Mixing a chemical herbicide with non-pressure liquid nitrogen and applying it preplant. postplant or postemerge is popular in many areas (the so-called feed-n-weed technique). High-pressure gas and low-pressure liquid forms of nitrogen must be injected or incorporated into the soil to minimize losses., They can be .applied during a primary tillage operation by fitting the mold- board or chisel plow with distribution hoses to release the material below ground (a supply tank is usually mounted on the tractor or plow. or a nurse tank is pulled behind the plow). These materiakzmay also be applied with a special knife-down applicator. either in the spring (usually preplant on plowed ground) or after the corn has emerged (this method is called sidedressing). Harvesting and marketing is yet another phase of the corn production system in which alternative technologies abound. Each one has special implications regarding equip- ment sizing. selection and scheduling. and overall system performance. The farm manager may chose to harvest all or part of the crop in a number of different forms: as whole- plant corn silage. as ground ear-corn silage. as standard ear corn. or as field-shelled corn. In each case a trans- port system of some type is usually maintained. under con- trol of the farm manager. to move the harvested material from the field. In the case of shelled corn. the transport system us- ually consists of farm trucks. wagons pulled by tractors. or a combination of these two. The specific makeup of the transport system may depend on where the corn is going (to a farmstead or direct to an off-farm market). But other factors also influence the number and type of transport vehicles employed. These include such things as harvesting capacity. grain tank size. combine unload points in a particular field (affected by yield. moisture content and row length). method of transfer from the combine (stop un- loading versus on-the-go unloading). and the"turn-around" time at. and travel times to and from the delivery point. If corn is to be dried at the farm and then marketed off- farm. either at harvest or at a later date. then the farm manager must arrange for it to be moved by custom haulers. or provide the necessary transport capability himself. On-farm drying of shelled corn may also be done in various ways. These include in-bin layer drying. batch-in- bin drying. portable batch drying and continuous flow dry- ing. Another alternative includes the use of dryeration with batch and continuous flow driers.* Each method has certain capacity limitations and each has special handling facility requirements (dump pit. conveyors. wet holding. dry holding. etc.) for a good "match" with a particular harvesting and hauling system. The alternative technologies and modes of operation just cited. plus a host of others, are all being used in varying combinations on farms throughout the corn belt. Usually no two farm managers employ or utilize precisely the same set of technologies or operating policies. Similarly. no two farms are identical in terms of labor and other resources. or in terms of physical makeup and location (with the implicit effects on system performance which these factors carry with them) 0 * The corn is only partially dried in the drier. then trans- girred "hot" to a separate "steeping” and (slow) cooling n. If a computer simulation model of the corn production system is to be of practical significance as a management tool to all but a few select farm managers. then it must be highly user-specific. That is. it should have the capability of dealing with various resource and land base configurations. a variety of land. equipment and labor policy options. and at least the major technological variations in production. harvesting and marketing practices. The development of such a model. to "deal with" these various factors. can be done in a number of different ways. The purpose of this study was to explore a particular way of doing it. namely that of using event-oriented simulation techniques. * The corn production system is conceptualized as a set of mobile discrete objects (men. tractors. com- bines. trucks. etc.) that interact with a set of immobile discrete objects (fields. drying equipment. off-farm mar- kets. etc.) based on a set of policy and procedure rules (some of which would be Specified by the model-user) to accomplish the desired production. harvesting and market- ing activities. Such a scheme would. of necessity. involve a rather de- tailed analysis (and knowledge) of the real-world activities to be simulated. It was envisioned. for instance. that a * The term event-oriented simulation will be used and under- stood to be synonymous with discrete-event or variable-time increment simulation. i.e.. simulated time is sequentially advanced to the time of occurence of the next imminent event. as opposed to continuous time or fixed-time increment simulation techniques. 1O typical sequence of activities at the beginning of a simu- lated day. for a particular piece of field equipment and its operator. might be: prepare the equipment. move to the field. begin ”on-row” operation. stop for adjustment. continue operation. turn at the end of the field. continue operation. etc. Concurrent with these activities. a second operator in the system might be doing the following things: prepare a itransport vehicle. move to a production supply point or corn delivery point. load production supplies or unload corn left on the vehicle overnight. move to the field and position the vehicle for the next materials handling job (outflow of production supplies or inflow of harvested corn). wait at this position if materials handling is not immediately re- quired. etc. For one-man systems. a single operator would perform both sets of activities: being assigned first to the trans- port vehicle. and then to the field equipment. For multi- man systems. two or more operators might be assigned to per- form the same or different field operations with different sets of equipment. while simultaneously other men might be assigned to perform transport activities. on-farm drying or grain handling activities. and so forth. The following model requirements were identified: 1) It should provide the capability of realistically accounting for certain ”non-productive” time re- quirements that occur in the real world on a determ- inistic or stochastic basis. 2) 3) 11 It should permit realistic (simulated) scheduling of two or more activites that compete for the same men and/or machines. It should allow the model-user to realistically evaluate various equipment combinations and management policies with a minimum of a priori knowledge. The first zeqfirement implies modeling such things as the time required for out-of-field equipment movement (determin- istic). and the time required for equipment repairs and/or adjustment. plus their actual time of occunence (stochastic). The second requirement implies modeling: 1) 2) the allocation of resources among the various functions needed to accomplish a given field activity on a given day. e.g.. the field operation itself (corn combining. for instance) vs. supporting trans- port activities (hauling corn. for instance) vs. supporting farmstead activities (dryer operation or grain handling. for instance). and the allocation of resources among two or more field activities (and their support functions) that might be performed on a given day. e.g.. land prepar- ation vs. planting vs. crop-tending field operations in late may. or harvesting vs. fall tillage activities ‘ during the harvest season. The third requirement noted above implies a particular for- mat for input specifications for field operations and other 12 activities to be simulated. With continuous time simulation techniques. for instance. modeling is usually based on average rates of accomplishment or performance. e.g.. field capacities in acres per hour or harvesting rates in bushels per hour must be given. If the model-user. then. is to deter- mine the overall impact of using a larger combine. of using on-the-go combine unloading instead of stop-unloading. of using a different corn transport system. or using a new drying facility. etc.. then he must assume that his labor and equip- ment will be able to perform in a particular way in order to specify the average performance rates needed as input. With the proposed approach in this study. using event-oriented simulation. however. the model-user must provide only the more basic operating specifications such as preferred (or attainable) on-row equipment speeds. travel and transport speeds. handling rates. etc.. plus the desired mode of operation. The simulation model. then. not the model-user. determines "how well” the labor and equipment is able to perform. i.e.. it computes the average performance rates on specific days. when operating in specific fields. or for the farm as a whole over a specific season. This could be an important distinction between the two modeling approaches. especially far the following: 1) For large operations that are composed of a number of non- contiguous land bases (where a good deal of road travel is involved in moving equipment. supplies and harvested corn). 13 and 2) For those aspects of all systems that depend on a meshing of two or more distinct equipment and labor sub- systems. e.g.. a corn harvesting subsystem. a corn trans- port subsystem and an on-farm drying and handling subsystem (where the corn-flow output from one subsystem is the corn- . flow input to the next). It has been suggested that event-oriented simulation. and the amount odeetail it requires is necessary only to evaluate equipment and policy decisions that could at best have a minor impact on the overall performance and profita- bility Of a corn_production. harvesting and marketing system. This may well be true. Until the present time. however. a simulation model had not been developed with the capability of realistically evaluating these ”minor" equipment and policy decisions -- ones which farm managers Egg making decisions on. without the help of such a management tool. REVIEW OF LITERATURE Machinery Performance Measures The theoretical field capacity of a machine (TFC). in acres per hour. is SW/8.25 where S is the forward travel speed (in miles per hour) and W'is the rated width of cover- age (in feet). The effective field capacity (EFC). in acres per hour. is the actual (or demonstrated) average rate of coverage or accomplishment by the machine based upon total field time. Field efficiency (E) is defined as the ratio of the effective and theoretical field capacity. expressed as percent. i.e.. E = 100 EFC/TFO. Effective field capacity is a commonly used measure of field machine performance in farm machinery management studies (selection. scheduling and replacement problems) to predict machine and labor time requirements. To do so the investigator normally uses the generally accepted equation EFC = SUE/8.25 (McKibben. 1930. Kepner gt 31.. 1972. Agricultural Engineers Yearbook. l97h). where E is assigned a value based on the type or category of machine. or the conditions under which it will be operating. Out-of-field time requirements are sometimes brought into the study by simply adding some per- centage of the field time for the particular operation (Stapleton and Hinz. 1974). 14 15 The effective field capacity of a machine will always be less than its theoretical capacity -- field efficiency will always be less than 100% -- due to time lost in the field and failure to utilize the full width of the machine.‘ Because of its importance to farm machinery management. con- siderable research has been conducted to determine field efficiencies for agricultural machines. Data available prior to 1971 have been summarized and reported in the Agricultuggl Engineers Yearbook (1974), where a typical range in values is given for most types of machines. ' Time loss in the field is due to turning and idle travel. materials handling activities. cleaning. unclogging and ad- justing machines. lubrication and refueling (over daily service). and waiting on other machines. Field efficiency is not a constant for a particular machine. but varies with oper- ator capability and habits. operating policy. and field or crop conditions. For instance. a greater prOportion of total field time will be needed for turning in a field with short * A common assumption is that row-crop machines utilize 100% of their rated width. whereas open-field implements with spaced functional units are subject to losses from overlapping (Kepner et al.. 1972). The first part of this assumption is true only if the rated width of the planter and postplant row- crop machines are computed as Nw. where N is the number of rows covered or processed. and w is the avera e row width. The average row width may be slightly less (more) than the measured center-to-center distance between adjacent rows of a cultivator or combine cornhead (or between units on the planter). due to "mis-setting" of the planter marker device or driving "errors". or both. whether planned or unintentional. Some farmers consistently ”crowd” the marker. especially with wide-row planters. to produce an average row width that is one or two inches less than the planter setting. 16 rows than in one with longer rows. all other factors being the same. Renoll (1969) found that rough or narrow turn areas can increase turning time as much as 50%. Barnes gt gt. (1959) found a similar increase in average turning time for 6-row cultivators and planters compared to h-row units. Stapleton and Hinz (1974) suggest that realistic times for semicircular turns can be computed as ( W/88s) + (w/ho), where s is the speed of travel of the outer end of. the machine (mph). The w/hO term is a "lag time” allowed to lift the machine before the turn and lower it again after the turn. Materials handling activities can produce significant amounts of lost time in field operations. Handling bagged materials can easily occupy 25% of total field time in planting-fertilizing operations (Kepner gt gl.. 1972). Renoll (1970) found a nearly 15% increase in planting capacity when the method of transferring water to the planter tanks for chemical application was improved. Stapleton and Hinz (1979) illustrate how cotton picker capacity might be increased about 3 % by eliminating the extra time required to "overfill" cotton trailers. Research studies on field machine and transport system interrelationships. and their affect on field capacity and efficiency are quite limited. Von Bargen (1970) used simulation to evaluate corn planting systems. including supply transport and handling activites. for 19 Indiana 1? farms. Thesimulated field efficiencies were all within the range of typical values reported in the Agricultural Engineers Yearbook (1974). Determining Machine Performance Time studies have been made by a number of investigators to determine field efficiencies and provide informmion for operations analysis. If only the field efficiency is desired. one can observe the total field time for one or more days. the average speed for performing the operation. the total acres covered. and the rated width of the machine (Kepner gt_gt.. 1972). The actual average rate of coverage can then be related to the theoretical field capacity to determine the field efficiency. Such a study yields but a single field efficiency value for the particular set of circumstances for which it was obtained: a particular machine and operator. field size and shape. operating procedure. field or crop condition. etc. A more useful technique is to carry out detailed time studies of the various activities involved in the field operations (and/or related out-of-field activities). The type of activities timed would depend on the type of field operation under study. Planting. filling boxes, turning and delay time for adjusting. cleaning and checking the planter were used by Barnes gt gt. (1959) to compare h-row and 6-row corn planters. Renoll (1966) used activities of adding seed. fertilizer and water. adjustment and downtime. turning and jplanting to study factor's affecting the performance of 18 cotton planters. In a later study. Renoll (1970) obtained activity times for a cotton picker in the categories of picking. turning. dumping basket. cleaning machine. idle travel. travel to and from wagon. packing basket and other downtime. Geyer (1963) defined nearly 100 different activities related to corn harvesting and handling opera- tions. Von Bargen (1968) proposed the five basic activities of operate. delay. travel. service and idle for describing the performance of a field machine for any scheduled period. Using the results of such studies. models can be developed to synthesize the machine (and system) perfor- mance and field efficiencies for the almost limitless com- binations of conditions and circumstances under which farm machinery is (and is likely to be) used. Renoll (1972) pro- posed a simple model for predicting machine performance in a particular field based on a minutes-per-acre concept for operate. turning and ”support" functions. Von Bargen (1970) developed a stochastic simulation model for evaluating the performance of planting. materials transport and handling systems. The use of models for analyzing agricultural machinery systems is presently limited by the lack of data characteriz- ing primary and support activities for field operations. and for other facets of the system as well. Energy consumption. functional performance. capacity. costs of all kinds and interactions among system components are the kinds of data needed (Stapleton and Barnes. 1967). 19 Simulation Languages There are at least two broad classes of computer simulations (Manetsch. 1969): "One claSs. called " discrete" simulations. takes a microscopic view of the world and models individual system entities or events. whatever they might be -- individual carriers or arrivals in a transportation system. individual units in a production process. etc. A second important class. called ” continuous flow" simulation. essentially takes a macroscopic view of the world and models a system in terms of flows or aggregates of basic system entities or events -- flows of physical output. streams of income. and so forth." A number of so-called "simulation languages" have been developed to simplify the task of writing simulation programs for a variety of different types of models and systems (Naylor 91; a1... 1966).* These include DYNAMO and CSMP for continuous flow simulations. and GPSS. SIMSCRIPT and GASP for discrete simulations.** The simulation languages GPSS and SIMSCRIPT are used more frequently than * Sammett (1969) states that programming languages have become the major means of communication between the person with a problem and the digital computer used to help solve it. The most well known language (FORTRAN) is merely one of approximately 120 languages he describes. Of these. about 20 are completely dead or on obsolete computers. 35 are receiving very little usage. 50 are for specialized application areas. and 15 are widely used and/or implemented (circa the fall of 1967). ** Several versions of many programming languages have been developed with special features and/or for use on particular computers. e.g. CSMP/360. CSMP/ll30. SIMSCRIPT. SIMSCRIPT 1.5. SIMSCRIPT II. GPSS. GPSSII. GPSS/360. GASP. GASP II. GASP 11a and GASP IV. Some programming languages developed initially for discrete simulations, may have. with subsequent versions. the capability of handling continuous flow simulations. 20 GASP. FORTRAN and other languagesfor simulation pro- gramming in the United States. while SIMULA and CSL are monapopular in EurOpe and Great Britain (Pritsker and Kiviat. 1969). The simulation language best suited for a particular study depends upon the nature of the system and upon the programming skill of the individual conducting the study (Naylor gt gt.. 1969). For example. GPSS II is best suited to certain types of scheduling and waiting line problems. while DYNAMO is best suited to simuladons of large-scale economic systems that are described by models involving complex ‘feed back mechanisms. Pritsker and Kiviat (1969) present the following discussion of the GASP II. SIMSCRIPT and GPSS/36O programming languages used for discrete simulations. Concerning static modeling concepts they state: "GASP II views the world as composed of entities that are described by attributes and related through files. A system state can be changed only if entities are created or destroyed: attribute values changed: or file contents altered. Existing in a FORTRAN framework. GASP II treats the creation and destruction of new entities logically. rather than physically. by keeping track of available columnsin arrays. Arrays are used for storing attributes of entities as well as files of entities. SIMSCRIPT also deals with entities and attributes but substitutes a more general device called a ggt for the file. Entities are divided into two categories, temporary and permanent. Temporary entities are physically created and destroyed through special statements. Permanent entities have their attributes 23%E%gegsc§fir%¥i5ngB%ghsgigpgfiarxwfinge gfmaSIMSCRIPT. like GASP. uses pointers to chain together entities that are members of sets: i.e.. thatare contained in 1193. 21 GPSS/360 deals with objects called transactions. facilities. and storages. Transactions have parameters that describe them and are generated and terminated dynamically. Facilities and storages represent permanent entities and have capacity-limited properties. Transactions may be grouped together into user chains. which can be manipulated like files and sets. Any system modeled in SIMSCRIPT or GPSS/360. therefore. bears a strong relationship to a GASP II model as far as its static state model is concerned. It is not difficult to translate such a GASP model into SIMSCRIPT or GPSS/360 or vice versa. However. difficul- ties exist in modifying other features. For example. in GASP several attributes cannot be packed into one computer word. Translation may even be impossible. although usually something can be worked out except in the largest or more complex simulation." Concerning dynamic modeling concepts they state: ”GASP II is concerned with events that occur at points in time at which system state changes take place. Events are represented by computer programs that make state changes. query the system about its past and present. and perhaps forecast its future state. The programs also schedule future state changes to take place through other events. SIMSCRIPT has a concept similar to that of GASP. A SIMSCRIPT program contains an events program and event subroutines. But. in addition. SIMSCRIPT contains a mechanism for automatically scheduling exogenous events(externally caused events) by special exogenous event data cards. GPSS/360 takes a different view of system dynamics. A GPSS programmer does not write a program in the same sense as a GASP or SIMSCRIPT programmer does. Instead. he constructs a block diagram made up of 45 different types of blocks. each of which.performs a special simulation-oriented function. A GPSS pro- grammer prepares a block diagram by visualizing how a typical transaction will flow through a system. Some blocks.such as ADVANCE. represent time delays. The GPSS system generates a calendar of events to make them happen. Other blocks, such as SIEZE. represent logical operations and are executed without delay. All GPSS programming takes place in the context of these 45 blocks. just as GASP II programming takes place within the context of FORTRAN and the standard GASP II subroutines and functions. 22 Translations between GASP II and SIMSCRIPT. therefore. are quite direct. Translations between either GASP II or SIMSCRIPT and GPSS/360 are more difficult. Although GASP II and GPSS/360 models may have the same static structures. their dynamic models are completely different." Naylor 22.§l- (1966) make the following observations about discrete simulation languages: GASP represents a completely different concept in simulation languages than that offered by GPSS II and SIMSCRIPT because it is written in FORTRAN and can therefore be recompiled using any FORTRAN compiling system available to a particular analyst. Most simulation languages have been written exclusively for large-scale computers (of the magnitude of the IBM 7090/ 94). The fact that GASP is written in FORTRAN. a universal scientific programming language. the programmer is not likely to find it necessary to learn a new language or obtain a compiler whidlis not readily available for his particular computer. Programs written in GASP consist of a FORTRAN "main program" associated with an elaborate set of FORTRAN subroutines which when combined yield a very powerful simulation programming package. The advantage of this modular approach is that each person can design his own simulation language in a manner that is best suited to his particular simulation requirements. 1. 2. OBJECTIVES To develop a user-specific. event-oriented simulation model for corn production systems. To demonstrate the use of event-oriented simulation for corn harvesting. handling and marketing. 23 SYSTEM BOUNDARIES AND DESIRED MODEL CHARACTERISTICS The purpose of this study was to explore a particular model-development scheme: The use of event-oriented simu- lation with the discrete objects that comprise corn pro- duction systems. A number of system constraints and de- sirable model characteristics were established at the onset: 1) The model should be developed for an individual farming operation (an individual firm) that exists solely for the production of corn. There should be no competition for men. machines or field time from other crop enterprises. 2) The corn that is produced should be field-shelled using self-propelled combines. The use of ear-corn harvesting and handling equipment. and the use of tractor-mounted picker-shellers would not be considered. 3) The model should permit detailed simulation of gt; activities required to produce. harvest and market the corn crop. excluding the use of custom services. i.e.. those activities normally performed by the men and equipment under the direct control of the farm manager. This should include. in additionto normal field operations and related on-farm activities. such 25 things as the transport of production supplies (mainly fertilizer) to the farm from local off-farm supply points. if not done during the "off-season”. and the transport of corn from the farm to local off-farm market points.* 4) The model should be sensitive to weather-related factors that affect the performance of field acti- vities and the development and maturity of the crop. 5) The model should permit simulation of a single crops year or several sequential crop-years of activities. A single crop-year. it was recognized. might encompass up to three distinct calendar-years. e.g.. fall till- age in 1972. planting and harvesting in 1973. and harvesting and/or off-farm marketing in 1974. 6) The model should be compatible with and complementary to the basic modeling concepts and structural consid- erations previously developed by Holtman gt gt. (1970). This should include the use of daily weather data as input. the use of Special-purpose subroutines to perform often-repeated accounting functions. and * The movement of production supplies (seed. fertilizer. her- bicide. etc.) to the farm. and their placement into an on- farm storage structure should be assumed to occur if it is done at a time when it is not in direct competition with critical field activities. Similarly. the disappearance of farm-stored corn that is marketed through an on-farm live- stock enterprise should be assumed to occur. i.e.. the feed- ing activities related to the livestock enterprise should not be simulated. 26 the use of ”field sections" as the basic accounting unit for weather-related factors such as soil mois- ture. soil tractability. and various crop development items. MODEL INPUT CONSIDERATIONS The initial phase of the study was concerned primarily with the identification of user (farm manager) policy options and peculiarities that exist in the real world. and the selection of the most desirable ones to be included in the model development. A method of specifying these to minimize the burden for farm managers was then con-I sidered. In developing the input form (see Appendix .A ) an attempt was made to ask for information in a way and in terms that are commonly used or easily understood by corn producers. much of the information needed to physically describe the farm and certain field-related policy factors. for instance. is contained on. or can easily be added to. a scale map drawing of the farm under study. Most farm mana- gers maintain up-to-date field maps of their farms. It was understood that an intermediary would be needed to transform the information given on the input form into actual input data for the simulation model. Operating specifications for the farm are asked for in an approximate chronological order -- production. than harvesting. then handling and marketing. In general. four types of information are requested for each broad category of operating specifications: 1) What activities are to be 27 28 done. 2) What equipment is available to do them. 3) How are they to be done (special instructions or restrictions). and finally 4) How much labor is available to do them. Net all of the special policy options shown on the in- put form have been developed for the present model. Four basic handling and marketing Options, for instance. are shown: 1) on-farm storage of high—moisture corn. 2) in-bin layer drying. 3) batch or continuous flow drying. and 4) direct marketing from the field. Only the first and last options are possible with the present model. Information storage and model structuring. however. have been done in such a way that these other options can be developed and incorporated into the model at a later date. MODEL FORMULATION CONCEPTS AND MANAGEMENT POLICY OPTIONS Concurrent with the development of the input form came the formulation of certain basic modeling concepts needed to adequately deal with the desired user-options to be in- corporated into the model. Activity Period Concept The calendar year was conceptualized as consisting of six basic activity periods in which farm managers may want to perform certain types of field operations. These are: 1) the fall land preparation period. 2) the winter land preparation period. 3) the preplant or spring land prepara- tion period. 4) the planting period. 5) the postplant (crop tending) period. and 6) the harvest period. If desired. the model-user can specify field operations to be performed in each period. It is not necessary. however. to use all six activity periods. Some farm managers. for instance. plan no fall tillage work. Upon completion of the field operation(s) specified for a given period the current activity period number is automatically updated by the model to the next one in 29 30 which field operations are possible. Field operations for the new activity period may not be permitted. however. un- til certain other criterion are met. The planting and harvesting operations are always carried to completion. regardless of the calendar date or other factors. Field operations for activity periods No. 1.2.3 and 5 may or may not be carried to completion depending on the following: 1) Fall land preparation period -- This activity period terminates on the day the soil freezes in the fall if it is in effect on that day. Residue management. fertilizer application. and tillage operations are the primary activities to be carried-out during this period. Note that this activity period (1) for a given year. seque- ntially follows the harvest period (6) for the previous year. If harvesting extends beyond the soil-freeze date. then activity period No. 1 will not occur that particular year. The termination of activity period No. 1 marks the beginning of activity period No. 2. 3 or 4. depending on the next scheduled field operations. Activity period No. 1 (2, 3 or 4) begins the moment that the harvest operation is completed. 2) Winter land preparation period -- This activity period automatically terminates on the day the soil thaws in the spring if it is in effect on that day. Shredding stalks and spreading fertilizer (surface application) are the primary activities to be carried-out during this period. If the soil fails to freeze naturally during a mild winter. 31 then it is assumed to be“ frozen (and saturated with ground water) on March 1. The termination of activity period No. 2 marks the beginning of activity period No. 3 or 4. 3) Preplant or spring land preparation period -- This activity period is automatically terminated. if in effect. based on the preferred and mandatory start-planting dates (Dr,and Dug specified by the model-user. and the date on which the soil temperature reaches 50 degrees (D50). Acti- vity period No. 3 may terminate on -- Dm. if D1) a nu: or on D'p. if Dp avod coausHSSua Ir a me n .N hvu>wuos .u undue o: mom has a u wmaeos .omasmozvo : o» no .uoumoa pmo>msn on» ma maze NH m on mmduux pom .Smuov oHanwm>m poc ma momma m“ has. mmmaos omsmro mmmqoo onwvsomnsn oapwmmoa mouuw>upos : wmmao we canwmmoa moduw>apes m mama «a mapwmmoa mofivmbuvom mom N mmma .SOHmouHmo weaken th>wvom so comma oapmmmoa no: one mac can MM haze ~ on mmflwum um Amado _ mumfloew 60 Note that setting MCLASS a 2 only rules out the simulation of class 1 activities (fld ops) for the day. while class 2 or 3 activities may still be possible. Subroutine GOLABR next considers labor availability factors for the day. If labor is available. then MCLASS is unchanged (from its current setting of 1 or 2). and GOLABR sets MDAY n 1. 3 or 5 if today is a weekday. a Saturday or a Sunday. This MDAY-value will be used later to set the overall time limits for simulation if today is declared an activity-simulation day. In determining if labor is available. GOLABR may check up to three different labor schedules if activity period No. 4 (planting) is currently in effect. The model-user may specify different (or identical) labor schedules for the be- fore lay 3 time period. the may 3 - may 23 time period. and the after May 23 time period. If labor is not available. then today must be Saturday. or Sunday. since weekday labor is always available. and GOLABR will take the following action: 1) Set MCLASS a 3. MDAY = 1 if the harvest period (6) is currently in effect. 2) Set_MCLASS - 4. otherwise. The MCLASS - 3 setting will allow class 4 activities (on- farm drying and handling only) to be simulated today. if they are needed. using the harvest-time. weekday labor sche- dule. The MCLASS a 4 setting is a special signal that no activity-simulation of any kind will be allowed today since labor is not available. 61 If MCLASS is still set at 1 (fld ops still possible) after considering labor. then the snow depth for the day is checked. The snow-depth criteria (currently set at 3 inches) is defined in subroutine SETCON. Its purpose is to prevent harvesting and other activity period No. 1 and 2 fld eps if the actual snow cover for the day is too great. If MCLASS is still set at 1 (fld ops still possible). then subroutine GOFLDS is called to determine if there is at least one field section somewhere on the farm in which a field operation of some type could be performed. If one cannot be found. then MCLASS is changed to 2. GOFLDS considers individual fld ops one at a time. During the planting period (4) and harvest period (6). it examines the planting fld op and harvesting fld op first. respectively. then considers other non-plant. non-harvest fld ops that might be possible. in the sequence they were loaded in the fld-op-status array. In order to exit subroutine GOFLDS with MCLASS = 1. a field section must be found which: 1) is ready. but has not yet received the fld op and. 2) is tractable. i.e.. the soil is able to support field equipment. ' Note that ”ready” implies a soil temperature of 50°F or greater prior to the mandatory start-planting date. for the planting field operation itself. Soil temperature is maintained for the farm as a whole. and is assumed to be the same in all field sections. "Ready“ also implies a 62 kernel moisture in the desired range prior to the mandatory start-harvest date when the fld op being considered is har- vesting. Recall that subroutine CORNMS set a ”ready" work- status for the field as a whole if at least one field section was in the desired kernel moisture range. The kernel moisture in individual sections must be examined if some harvesting has already been done in the field being consid- ered. All field sections are considered tractable if the soil is in the frozen state. If it is not. then subroutine TRCBL2. a modified version of Holtman's subroutine TRACBL. is called by GOFLDS. A single call to TRCBL2 sets the tractability state of all field sections in the farm. To declare a section tractable. the ratio of the actual available soil moisture to the maximum available soil moisture must be 0.95 or less in»the top 2 soil layers. For these soils classified as ”medium” or ”heavy”. this ratio must be»NVAL for MCODE the minimum value>NVAL for MCODE the maximum value‘1 Figure 6. Stats Changes in Simulated Time. intended for on—farm high moisture storage. and for direct from the field off-farm marketing are listed in Table 3.’ During activity-simulation. entities are advanced from state-to-state by the event routines. At the occurrence of each event. subroutine STATEI is called to record (store) the state-time information for each entity associated with the particular event. The amount of time that each entity has existed in each activity state is accumulated on an annual basis and on a field basis. For combines. for pro- duction equipment sets that apply no materials. and for those that apply materials but utilize an in-field supply vehicle. * The file 7 activity states are equally’ applicable to pro- duction and harvest equipment sets. and the file 8 activity states are equally applicable to transport sets involved in handling production supplies or in transporting corn. The (activity states proposed for the file 11 entities associated with on-farm drying are presented in Appendix D. 93 Table 3. Activity States Defined to: Equipment and Facility Entities.’ Type of Activity - Pile Entity State No." Type of Activity 7 Equipment 1 All cut-cf-ficld travel. Sets 2 Non-operate in-fisld travel necessary for the field pattern being used (turning at the ends. QtCe)e 3 Extra non-operate in—field travel. above normal field pattern requirements. needed to obtain production supplies being applied or to unload harvested corn. “ On-row operation. 5 Delay for refueling anybr maintenance. 6 Delay for repairs and/or machine adjustments. 7 Delay for materials handling -- taking on product- ion supplies. or transferring harvested corn to a transport vehicle. 3 All other delays with or without an assigned oper- ator present. 8 Transport 1 All out-oi-fieid travel. Sets 2 All in-field travel. 3 Out-of-field materials handling -- taking on pro- duction supplies or farm-stored corn. or unload- ing corn. 4 In-field materials handling -- transferring supplies to a production equipment set. or receiving corn from a combine. 5 Delay for refueling and/or maintenance. 6 Delay for repairs. 7 All other delays with an assigned driver present. 8 All delays with no assigned driver present. 11 Drier and 1 Non-operate or idle. Silo-Fill Tractors Operate or non-idle. 11 High MC 1 In—active (empty. partially filled.full). Storage Sites 2 Operate or non-idle. ' Activity states are not maintained for file 11 off-farm market entities. See Appendix D for the activity states proposed for {Lie 1! entities associated with on—fnrm drying. 7' These values may be assumed by the HST-attributes (see Appendix B}-NST1 for file 7 entities. HST: for file 8 entities. and NST3 for the file 11 entities indicated. 9“ Table h. Activity States Defined for Labor Entities. Labor State No. Equipment or Activity Assignment 1 Assigned to a non-harvest equipment set. 2 Assigned to a harvest equipment set (corn combine). 3 _Assigned to a production supply transport set. Assigned to a corn transport set. All other assignments -- operating the drying and handling equipment at an on-farm drier. site. moving the filling equipment from. one silo to another at a high-moisture stor- age site. or refuel and maintenance activities for field equipment on non-field-work days.” !' Labor time is accumulated in states 1 through # for re- fuel and maintenance activities on field-work days. the traditional measure of field efficiency (%) is 100 x (time in state h)'+ (sum of the times in states 2 thru 8). Activity time for labor. the file 6 entities. is main- tained separately from equipment time. The labor states. and time records maintained. are listed in Table h. materials handling attributes A total of eight different non-fuel materials were identified as being potentially important for event-oriented activity-simulation. These are the Q1...Q2.., etc. attributes defined in Appendix B. where the single-digit numbers indicate 95 the material ”type" code numbers used (see the input form also. Appendix A). _ In general. corn attribute values (material code 1) are important for combines (files h and 7). transport vehicles used to haul corn (files 5 and 8). and for all of the non-tractor entities in file 11 -- dump pits. conveyors. holding. cooling and drying bins. driers. and storage faci- ilities. both on-farm and off-farm. Production material atr tribute values (material codes 2 through 8), however. are necessary only for production equipment sets that apply mat? erials (file 7). and for the transport vehicles that supply them (files 5 and 8). The attribute values maintained for corn are on the basis of equivalent bushels of No. 2 corn. i.e.. bushels of corn at 15.5% kernel moisture (wet basis). These include the holding capacity and flow-rate specifications supplied by the model-user. and the "current level" attributes generated and maintained by the model. Where the current corn level is an important factor in determining activity and event times. a moisture content and actual volume attribute value is also maintained. since the space occupied by a given quantity of corn depends on its moisture content. An equation developed by Herum (1962) was used to approximate this volume-moisture relationship: where V is the volume (in eubic feet) that would be occupied by one bushel of No. 2 corn (15.5% moisture) if it were at a moisture content of M (decimal. wet basis). 96 The significance of this relationship with event- oriented simulation is illustrated in the following two examples: 1) A 6-row. 30-inch corn combine with a ”loo-bushel” - grain tank is tohmwest a field that will yield 125 bushels of No. 2 corn per acre. If harvest- ing is done at a kernel moisture of 20%, then the combine must travel 126 rods to "fill” the grain tank. If kernel moisture is 25% at harvest. all other factors being the same. then the combine must only travel 111 ' rods to ”fill” the grain tank. This could mean the difference between being able to make a complete round in the field. and thereby needing transport vehicles only at one end of the field. and 22: being able to make a complete round. and thereby needing a transport vehicle at both ends of the field or a single unit positioned midway through the field. So it has implication for such things as the number of trans- port units required. the frequency of combine un- loading activities. the feasibility of using certain field patterns. etc. 2) The corn harvested in this same field is to be hauled away from the combine in a "350-bushel' truck. If the size of the field is 20 acres. then 9 "truck-loads" must be hauled away at the 25% moisture level. while only £3 ”loads" must be hauled at the 20% moisture level. Production material attribute values are defined some- what differently for equipment sets than for supply vehicles.‘ This difference is based partly on the following assumptions and model-user restrictions:** 1) Non-planting production equipment sets may apply a maximum of one material. 2) Planting equipment sets may apply a maximum of four materials. and must a ply a minimum of one -- seed corn (material code 6). * Proposed to be defined differently. since non-harvest acti- vity-simulation was not developed for the present model. ** And partly on the desire to minimize computer storage space requirements. both in the X-array and in the GASP files. 97 3) The carrying capacity (tank or hopper size). the application rate. and the supply source used for a particular material is closely associated with the field operation involved. and with the par- ticular way in which field equipment is assembled to perform the field operation (and apply the material). 4) The depletion of any material carried on and applied by an equipment set can signal the need for a "refill" activity for the equipment set. 5) Only the depletion of "high-volume-use" materials carried on an in-field supply vehicle can signal the need for a ”refill” activity for the supply vehicle. The high-volume-use materials were ident- ified as water (material code 2) used as a carrier for pesticides. and fertilizers (either bagged -- material code h. or bulk -- material codes 3 or 5).* If a transport vehicle is used to supply the plant- ing operation where seed. dry herbicide and ferti- lizer are being applied. for instance. then only the depletion of the fertilizer supply on the vehicle can signal the need for a vehicle refill activity. i.e.. it is assumed that the vehicle can carry enough seed corn and dry herbicide to last until the next fertllizer refill is needed. at which time the seed and dry herbicide supply carried on the vehicle would also be replenished. 6) Material transfer rates, and thus the refill time requirements, vary widely in practice only for bulk materials (water and bulk fertilizer). and depend on the particular materials handling techniques and equipment employed by the farm manager. The mater- ial transfer rates for bagged fertilizer. seed corn. dry herbicide. etc.. which require manual handling. will be approximately the same for all corn product- ion systems. Based on these factors. the model-user is required to specify the material type. the carrying capacity and appli- cation rate (in consistent units), and the supply source for ‘aJJ.production equipment sets that apply materials (see input :form, Appendix A). These attribute values. plus current _— ‘* It was assumed that farm managers would not require a single in-field. planter-supply vehicle to carry two different types of bulk fertilizers. 98 material levels. should be entered and maintained in the GASP files ggly_when the particular production equipment is assembled in file 7 for the performance of the field Operation. Excessively high values (999999.0) should be entered in the material-level attribute cells that are not required. since current material level can be used to indi- cate the need for a refill activity. If an in-field supply vehicle (not maintained by a dealer) is indicated as a supply source for any material to be applied. then the model-user must also provide information about it. This includes. if applicable. the on-off material transfer rates and/or carrying capacities of high-volume-use materials (in units consistent with those specified for the equipment set). These values become permanent attributes of the transport vehicle (:11. 5). material transfer rates must be assumed (and incorporated into the event-routines) for all materials other than the high- volume-use materials supplied by a farm-operated. in-field supply vehicle. Transfer rates must also be assumed for the high-volume-use materials. i;_an equipment set must leave the field for refills. .Fuel attributes Two fuel-related attributes are associated with all self- ‘propelled equipment units (tractors. combines and trucks): 1) fuel tank capacity (supplied by the model-user). and 2) current fuel level (generated and maintained by the model). jFor tractors and combines the model-user must also indicate 99 the fuel type. whether gasoline. diesel or LP-gas. All trucks are assumed to have_gasoline engines. During activity-simulation the current fuel-level attribute of a file 7 or 8 entity. or of a tractor doing farmstead work (file 11) is adjusted at the event times based on the entity's activity state (see activity states in Table 3). Equipment sets were assumed to consume fuel when in .activity states 1 through 4. tran5port sets in activity states 1 and 2 . and farmstead tractors in activity state 2 only. The fuel used for materials handling operations with equipment sets (state 7) and with transport sets (states 3 and b). if any. was neglected. Subroutine FUEL was developed to compute fuel-use rates (in gallons per hour) for the various types of entities when engaged in various activities.* For instance. estimates of tractor fuel consumption when using the different types of field implements (on-row operation. state a only) were stored in subroutine FUEL as the gallons of gasoline per hour per foot of implement width (assuming typical speeds). If the tractor is pulling two implements. then total fuel use was assumed to be the sum of the individual implement require- ments. A conversion factor of 0.72 for diesel fuel and 1.20 for LP-gas is applied when the tractor is not gasoline powered. * The adjustment (reduction) in current fuel level for the entity at the occurrence of a given event is (G x T) gallons. where G is the fuel-use rate computed by subroutine FUEL in gallons per hour. and T is the total elapsed time in hours since the entity last changed activity states. i.e.. the total time in hours since the last event involving this entity occurred. 100 Except for corn combine harvesting. which was estimated at 0.055 gallons of gasoline per hour per rated engine horse- power (on-row operation. state a only). all other fuel con- sumption values were estimated on a straight gallons (of gasoline)-per-hour basis. These included estimates for corn combine transport (non-operate travel). truck transport (corn or production supplies). and tractors engaged in 1) implement transport (non-operate travel). 2) hauling corn or production supplies. 3) PTO crop drier and forage blower operation. and h) PTO grain conveyor operation. . Fuel consumption for corn and production supply transport activities was assumed to range from 80 to 100 percent of the base fuel-use rate stored in subroutine FUEL. depending on the amount of actual loading at the time. i.e.. depending on the ratio QHAUL/QMAX. where QHAUL is the actual bushels of corn or pounds of production supplies being hauled. and QMAX is the maximum bushels of corn or pounds of production v supplies that could be hauled. Values specified by the model- user were used for QMAX. except for the case of a tranSport set composed of a tractor and one or two wagons engaged in hauling corn. In this case. it was assumed that QMAX was a function of the tractor sizes QMAX (bushels) = 2 * HP + 50. where HP is the rated PTO horsepower of the tractor. EPM attributes‘ An EPM attribute (extended-period-maintenance attribute) is generated and maintained by the model for each self 101 propelled equipment unit (each tractor. combine and truck).* The EPM attribute value of a given entity indicates the accum- ulated hours of use that remain for that entity before an EPM activity will be needed. During activity-simulation the RPM attribute value of an entity is reduced each time it is engaged in a fuel- consuming activity. e.g.. activity states 1 through 4 for equipment sets (file 7). states 1 and 2 for transport sets (file 8). and state 2 for tractors performing farmstead work (file 11). This is done at the event times. by an amount equal to the total elapsed time since the entity last changed activity states. i.e.. the elapsed time since the last event involving this entity occurred. When the EPM attribute value becomes zero or negative. the need for an EPM activity is indicated. With the present model. this is checked only at the start of each activity-simulation day. Initial EPM attribute values are assigned to each unit when the unassigned equipment files (files 2. 4 and 5) are created by initialization subroutine MACHRY. The actual value used is obtained from subroutine MAINT. During this initialization. subroutine MAINT also gener- ates and stores an EPM schedule for each tractor. combine and 'truck. With the present version of MAINT. the EPM schedule generated for tractors in the 100+ PTOHP category. for ex- ammple. is: * See page41 for a general discussion of daily vs. extended- period maintenance. 102 H1: 50 hours T1 = 0.50 hours H2-100 hours T2 = 0.75 hours H3-200 hours T3 = 1.25 hours Hnn800 hours 2.25 hours *3 :- II where H1 indicates the service interval and T1 the corres- ponding expected value of man-time required to perform the EPM activity. This particular EPM schedule can be inter- preted as follows: each 50 hours of operation a type 1 RPM activity requiring 0.50 hours of man-time will be needed: each 100 hours of operation a type 2 EPM activity requiring 0.75 hours of man-time will be needed; etc. Subroutine MAINT is designed so that different EPM schedules could be generated and maintained for each of the 9 tractor sizes with each of the 3 fuel types available. for each of the fuel types available with combines. and for each of the # different types of gasoline-powered trucks. i.e.. a total of 3“ different EPM schedules can be handled by subroutine MAINT. At the moment. only five different EPM schedules are being used. These apply to 1) tractors with less than 50 hp. 2) tractors with 50 - 99 hp. 3) tractors with 100 hp or more. #) combines. and 5) trucks. During activity-simulation. subroutine MAINT is called only when an EPM activity for a particular tractor. combine or truck is to be scheduled. i.e.. at the start of the next activity-simulation day following the activity-simulation day on which the EPM attribute value for the entity became Zero or negative. MAINT updates the EPM schedule for the Particular entity. it determines the reset value for the 103 EPM attribute. and it determines how much man-time will be required for the EPM activity to be scheduled. The man-time required. and thus the duration of the EPM activity will depend on the type of EPM jobs needed. For instance. with the RPM schedule given above. a type 1. 2 and 3 EPM job will be needed at the end of 200 hours of operation. Subroutine MAINT sums the expected values of the man-time required for each (Tsum)o and sets Tsum 2 maximum (0.5.T3um. T1). where 1 = 1. k (k 5: 2). Tsum 13' unaltered if k = 1. i.e.. if only one EPM job is needed '(which is possible with the EPM schedule given above at 50 hours. 150 hours. 250 hours. etc.). This model assumes that certain EPM jobscnum be done concurrently. e.g.. while one is waiting for the old transmission fluid to drain completely. he might be performing another needed EPM job. It is then assumed that the actual man-time required for the EPM activity to be scheduled (Tepm) may range from 80 to 120 percent of the computed Tsum- Subroutine MAINT then computes the actual duration of the EPM activity to be scheduled as Ter = TBum (0.8 + 0.0 e R). where R is a 0-1 uniformly distributed random number. Repair attributes Two types of repair attributes are generated and main- tained by the model for each self-propelled equipment unit (each tractor. combine and truck). for each implement avail- able for performing field operations. and for the farm- 8'tead equipment that. with use. is normally subject to Mechanical failure or malfunction. These are the RMAJ and RMIN attributes listed in Appendix B. corresponding to the 100 hours of use until the next major repair and minor repair. respectively. Repair attributes E22 not maintained for non- powered transport vehicles (trailers and wagons). Separate repair attributes Egg maintained for combines (the base units) and for combine cornheads (attachments to the base units). The distinction between major and minor repairs was made as follows: major repair -- An operating interruption that may require special skills. repair tools and/or parts not readily available on the farm for its correc- tion. The operating interruption (which may be 1. 2 or more hours in length) will be of suffi- cient duration that it may bring other equipment units to a standstill. e.g.. a major combine re- pair might eventually cause the transport sub- system and the on-farm drying and handling sub- system to cease operations due to a lack of corn. minor repair -- An operating interruption that can readily be corrected with the skills. repair tools and/or spare parts normally available or maintained on the farm. The operating interrupt- ion (which may be only a few minutes up to 40 or or 50 minutes in length) may be due to an actual mechanical failure or to the need for a simple adjustment of the unit. The operating time between repairs was assumed to be (negative) exponentially distributed with the expected values shown in Table 5. The duration of a repair activity was assumed to have both a deterministic and random component. the random component being (negative) exponentially distri- buted also. The deterministic components and expected values of the random components of repair time now being used for the Various categories of equipment are also shown in Table 5. 105 Table 5. Repair Attribute Factors. Equipment Major Repairs* Minor Repairs' -gategory RNEXT RTIME CMAJOR RNEXT BTIME CMINOR ’(hrs) (hrs) 4(hrs) (hrs) (min) (min) Tractor. gasoline 500 5 2 100 15 1 Tractor. diesel 700 5 2 100 15 1 Tractor. LP-gas 600 5 2 100 15 1 Rotary stalk chOpper 100 3 2 50 10 b Flail stalk shredder 100 3 2 50 10 h Moldboard plow 100 3 2 5 10 U Chisel plow 200 3 2 50 10 h Powered rotary tiller 100 3 2 50 10 4 Hvy. tandem disc 200 3 2 200 10 a Std. tandem disc 200 3 2 200 10 h Field cultivator 500 3 2 100 10 # Spring-tooth harrow 1000 3 2 100 10 # Row-crop planter 200 3 2 2 10 4 Rotary hoe 1000 3 2 500 10 h Row-crop cultivator 500 3 2 2 10 h Field sprayer 50 3 2 1 10 h Bulk fert. spreader 500 3 2 500 10 b Knifedown N appl. 200 3 2 5 10 4 Nitrogen nurse tank 1000 3 2 1000 10 4 Combine. gasoline #00 5 2 20 10 3 Combine. diesel #50 5 2 20 10 3 Combine. LP-gas 425 5 2 20 10 3 Combine cornhead 300 5 2 2 10 3 Trucks (all types) 2000 5 2 500 30 30 Dump pit. gravity** C6 0 0 C6 0 0 Dump pit. mechanical 100 1 1 50 15 10 Bucket elevator 500 -3 2 250 15 10 Auger conveyor 100 2 1 50 15 10 Belt conveyor 200 2 1 100 15 10 Other mech. conveyors 300 2 1 150 15 10 Gravity flow** 06 o o 06 o o Bin sweep conveyor 100 1 1 50 15 10 Burner and/or Low-r 200 1 1 200 15 1o fan + controls High'r 200 1 1 200 15 10 Int. Handling Equip. H: 200 2 1 200 15 10 * RNEXT = expected value of time between repairs: RTIME - ex- pected value of random component of repair time: CMAJOR/ CMINOR = deterministic component of repair time. ** C6 = 1,000,000 hours. t low = for dryeration bin. for batch-in-bin and for layer- drying bin; High a for portable batch or continuous flow driers. 1+ Integral handling equipment (augers. pressure switches. etc.) of portable batch and continuous flow driers. 106 management of the repair attribute values during activity-simulation is similar to that of the EPM attribute values in some respects. but different in others. Both types of attribute values indicate the ”accumulated hours of use" until the next EPM or repair activity will be needed. Both types are reduced at the event times by an amount equal to the just-concluded activity time for certain types of activities. With the RPM attribute this is done for all fuel-consuming activities. This is gen- erally true also for the repair attributes. except for equipment sets in file 7. Here it was assumed that ggly on-row operation (activity state #) contributed to reducing the time remaining until the next repair activity. i.e.. non-operate travel of equipment sets (activity states 1 through 3) does nothing to hasten the time of occurrence of the next repair activity. While the EPM attribute values are checked only at the beginning of each activity-simulation day. the repair attribute values must be checked throughout the day. at the beginning of each relevant activity. to see if the activity can be concluded without a repair interruption. The procedure is illustrated in Figure 7. and proceeds as follows: A particular event routine is ready to schedule an event that will signal the termination of an activity of duration Ta hours. The event routine has placed appropriate values in the ATRIB and JTRIB arrays in preparation for filing the event in events file 1. The 107 Case 1 -- Ta< Tr (a repair activity will not be needed) operate 4 a current clock time a duration of an activity about to be scheduled = smallest repair attri- bute value of the entity(s) a time required to com- plete the repair Case 2 -- 1'32 :rr (a repair activity wlll be needed) I I operate I I L¢+ mow + Tr stopped I for I repairs I I r» <3+TN0W+Tr+Td : operate fi I I k (I). TNOW+Ta+Td Figure 7. Scheduling of a Repair Activity 108 event routine. however. is designed to recognize that this activity is one which is relevant to the repair attributes of the entity (or entities) involved. i.e.. it is a relevant operate-activity. Before calling subroutine FILEM. then. the event routine calls subroutine RPRCHK. which examines the appropriate repair attribute values and sets Tr. the smallest repair attribute value found. RPRCHK then compares Tr with Ta. In case 1. Ta<:Tr. a repair activity will not be needed. so RPRCHK returns control to the event routine which files the event with an event time equal to TNOW + Ta. In case 2. Ta}? Tr: a repair activity will be needed. so RPRCHK calls subroutine REPAIR which generates Ta and a new repair attribute value ( to replace Tr at the conclusion of the repair activity). It then schedules the event which initiates the repair activity (at TNOW + Tr). it schedules the event which terminates the repair activity (at TNOW + Tr + Td). and it updates the ATRIB 800 JTRIB arrays so that. upon return to the event routine. the conclusion of the operate-activity can be scheduled with an event time equal to TNOW + Ta + Td.* *Actually this is not quite true. Before returning to the event routine. RPRCHK computes T5 = Ta - Tr (the amount of operate-time remaining after the scheduled repair activity; It then re-examines the appropriate repair attribute values. using the accumulated hours of use value generated by sub- routine REPAIR to replace Tr at the conclusion of the sche- duled repair activity. to see if another repair interruption will occur before the operate-activity can be concluded. If so. it files events to initiate and terminate the second repair activity. and repeats the re-examination procedure until all required repair activities have been scheduled be- fore returning control to the event routine from which it was called. -109 The deterministic components of repair times (see Table 5) are set by assignment statements in subroutine REPAIR. The random components of repair times (expected values) and the expected values of the time between repairs are stored in the X-array by initialization subroutine SETRPR. Event Control and Other Simulation Concepts When an activity-simulation day is declared in the daily simulation loop of Figure 1. subroutine MYSET is called to set the overall time limits for the day (TNOW and TFIN).* MYSET also schedules the first event of the day by placing an entry in the events file (file 1). The events file is ”empty” prior to this filing action. A call is then made to subroutine MYGASP. the master event-control routine for activity-simulation. Control re- mains with MYGASP until clock-time exceeds TFIN. or until one of the ”early” termination factors cited previously is encountered. This is recognized in MYGASP (see Figure 8) by the events file again being empty. i.e.. no more events to process. When the events file is non-empty. MYGASP removes calumn MFE(1). the first gntry in file 1. sets TLAST to 'the clock-time at which the last event occurred (TNOW be- fore the clock-time is updated). then takes a branch based —__¥ * TNOW. the master clock-time variable (current clock-time). if set to the earliest starting time for the current labor forcre, and TFIN. the ”target” completion time (clock-time) or 'the day. is set to the latest quitting time for the curlr‘ent labor force. 111) ( Subroutine MYGASP(NSET.QSET) ) yes (event file is empty) no (event file w is non-empty) CALL RMOVE(MPE(1).1.NSET.QSET) Remove the next event from the event file(1). i.e.. place its attribute values in the ATRIB-JTRIB arrays. where ATRIB(1 - event time JTRIB(1 - event sods I wuss . ruofl es dummy events) JTRIB(1) ‘ 95 ?? no(executive- .events CALL surmmss'rmss'r) , V 4 Store state-time CALL STATEZ(h'SET.QSET) information for the Process the dummy entity or entities event. associated with this event. a: lam. rvm-swraxsu ) .rs'ssrmssnj Call the appropriate event routine. VF Figure 0. Event Control with Subroutine IYOASPB 111 on the event code JTRIB(1). If the event is a "dummy“ event (discussed below). subroutine STATE2 processes it. If it is a ”legitimate” event. then the current clock-time TNOW is updated. state-time information is stored (by sub- routine STATEI) for ”real" events. and subroutine EVNTS is called. which in turn calls the appropriate event-routine. Eggnt types and attributes . Three types of events (or event code designations) were defined for activity-simulation. These are: Event codes 01-04 2 Executive events Event codes 05-94 = Real events Event codes 95-99 = Dummy events Subroutine MYGASP is designed to recognize these event types. and to process them accordingly. Executive events are initially filed at the start of an activity-simulation day by subroutine MYSET. These ini- tial executive events have but two attributes: ATRIB(1) = TNOW and JTRIB(1) - MCLASS. where MCLASS is the highest priority class of activities that may be simulated on a given dayt*' Subroutine MYGASP removes this initial executive event from file 1 (file 1 is now empty). defines TLAST and (rede- fines) TNOW. then calls subroutine EVNTS which in turn calls subroutine EXEC1. EXECZ. EXEC3 or EXEC4. ** These EXEC * Recall that MCLASS may be set to 1 -- field work. 2 -- general farmstead work. 3 -- corn marketing work. or 4 -- On-fifarm drying. handling and storage work on Sunday during :gekharvest season (the model-user did not permit Sunday P O " Gal); EXECI is operational with the current development. 112 routines initialize certain variables and arrays. assemble equipment and transport sets that will be needed today (files 7 and 8). assign men to various jobs. and file the first real events (file 1 is no longer empty) to start the activity-simulation. Real events are filed as needed by the EXEC routines and by the various event routines developed. Real events desig- nate the actual termination of one activity and the begin- ning of another for the entities involved. Real-event entries in file 1 utilize the attributes defined and the specific cell locations presented in Figure 9. At the event times. attribute value TNEW minus attri- bute TOLD is the total amount of time that the entities associated with the event have existed in their current state. Subroutine STATEl uses this time difference. plus the activity state values filed with the various entities to record (store)state-time information. Floating-point attribute locations 3 through 15 are utilized as needed for specific events. Examples are: the new x-y field coordinates for a combine or transport set when thlg event occurs. the amount of corn to be added to the combine's grain tank when thlg event occurs. the amount of corn to be transferred from the combine to a transport set when this event occurs. etc. The entity-ID information being filed. when needed. for corn harvesting events is generally positioned as follows: NTITYz - an operator (man) in file 6 Location QSET(1) messsuN NSET(1) urge ecse b) Figure 9. NTITY3 NTITYu NTITY5 NTITY5 113 Attribute TNEW TOLD ATT3 ATT15 JVENT NTITYZ O NTITY7 NACT Attributes of the Events TNEW TOLD ATTi JVENT NTITYi NACT Definitions: a Time of occurrence of this event. = Time at which the entity(s) associated with this event last changed state. = Attribute values needed for specific events. Event code number. Entity-ID informat- ion for the entity(s) associated with this event. Stored as AABB. where AA is the GASP column number. and BB is the GASP file number. = Current mode of op- eration indicator. File. a corn delivery point in file 11 the harvest field in file 10 a tractor doing farmstead work in file 11 the combine in file 7 a transport set in file 8 1511s information-storage technique provides a convenient nNathod of locating entity attributes during activity-simula- tion.* The combine's EPM attribute (fifth floating-point attribute value in file 7). for instance. is QSET (1+5). where \-—_ *A few event-routines developed utilize a afightly different POSitdoning scheme for the entity-ID information. e.g.. an eVent involving two transport sets requires two entity-ID Positions for the transport sets (one may be spotted in the *Eld and the driver transfers to another to move it to a d livery point). 114 I - (NTITY6/100-1)eIMM. the current activity state of the .transport set (eighth fixed-point attribute value in file 8) is NSET (J+8). where J = (NTITY7/100-1)..MXX. etc. The indicator (NACT) representing the current mode of IOperation may assume several values for corn harvesting events. These are: NACT - ABCDE A special start-of-the-day indicator that will be discussed later. NACT = 1 harvesting to ”open-up” a field. i.e.. harvesting turn rows prior to the start of “normal pattern” harvesting in a particular field. NACT = 2 Normal pattern harvest is proceeding away from the field-origin side of the field. NACT = 3 Normal pattern harvest is proceeding toward the field-origin side of the field. NACT = 4 End of the day. All activities now aimed at moving equipment units to their over- night storage locations. NACT a 5 End of the season. All activities now aimed at moving equipment units to their long-term storage locations. The concept of dummy events was developed so that in- active or idle (waiting) times associated with entities would lee accountable. Equipment and transport sets. for instance. nary be inactive at vadous times throughout the day: a combine Busy have to wait (activity state 8. file 7) for a transport set to return to the field: a transport set may have to wait (activity state 7 or 8. file 8) for the combine to complete 'an on-row harvest pass: a tractor that operates unloading equipment at the farmstead may have to wait (activity state 1. file 11) for a transport set to arrive: etc. When an 115 entity is placed into an inactive state. the clock-time at which it will be muvated again may not be known. Since there is no clock-time attribute associated with any of the non- event files (files 2 through 11). the dummy event technique provides the accounting capability needed. Dummy events utilize all of the fixed-point attributes shown in Figure 9. where JVENT designates the type of (in- active) entity: 95 96 = a farmstead equipment unit (and its assigned tractor)* an unassigned man in today's labor force 97 = a combine with or without an operator present 98 = a transport set with a driver present 99 Only the first two floaing-point attributes are used with a transport set without a driver dummy events. The program filing the dummy event sets TOLD = TNOW and TNEW = TNOW + 106. This gives the dummy event an event time (TNEW) that is artificially large compared to event times for real events. Thus. dummy events are filed at the "end" of the events file. "behind" any real events that are in file 1 at the time. or that are placed there later. Dummy events are routinely used during three specific phases of an activity-simulation day: 1) At the start of the day. The controling EXEC- - .routine for the day files a dummy event for all entities that are available for use or assign- ment at that time (after this determination has been made. of course). When the EXEC-routine * A grain conveyor. a drier. a high moisture storage facility. or a dry corn storage facility not at the drier-site. 116 files the first real event(s) to get the acti- vity-simulation started. it removes the dummy event(s) from file 1 for the entity(s) that will not be inactive when it returns control to sub- routine EVNTS. then MYGASP. 2) Throughout the day. Specific event-routines are designated to file and/or retrieve dummy events as needed as the activity-simulation proceeds. When a dummy event is removed from file 1. attribute TOLD always designates the clock-time at which the entity(s) became inactive. and TNOW minus TOLD is the total amount of inactive time. The event-- routines are designed to call subroutine STATE1 after removing a dummy event from file 1. which uses the time difference TNOW - TOLD to record state-time information for the entity(s) involved. 3) At the end of the day. The ”end-of-the-day” event- routines file dummy events for entities as they.are deactivated. For instance. the event-routine that handles the event signalling the completion of combine travel to its over-night storage location will file a 95 dummy event for the combine operator (if he is no longer needed) and/or a 97 dummy event for the combine. When all real events have been processed by subroutine MYGASP. all that will re- main in file 1 is a series of dummy events. repres- enting all entities that were available for use or assignment at the conclusion of activity-simulation. As these dummy events are removed from file 1 by MYGASP. subroutine STATE2 will call subroutine STATE1 to record the final state-time information for the day. After the last dummy event has been removed. MYGASP finds that file 1 is empty. and control transfers back into the daily simulation loop of Figure 1. Under normal circumstances. MYGASP should never remove a dummy event from file 1 except at the end of the day. If for some reason it does. subroutine STATE2 re-files the dummy event. setting attribute TNEW = TNOW + 106. but leaving attribute TOLD as previously set. i.e.. TOLD is always the clock-time at which the entity(s) became inactive. STATE2 recognizes this situation by examining attribute NACT. e.g.. if NACT ‘5 3. re-file the dummy event: if NACT 3' 4. do not 117 re-file it. Executive subroutine EXEgl Of the executive routines proposed for the four basic classes of activity-simulation days (field work. general farmstead work. corn marketing work. and on-farm drying.“ handling and storage work). only subroutine EXECI. for field 'work. is presently operational. and.only for corn harvesting and its associated support functions.“ In addi- tion. event-routines capable of carrying-out the event- oriented activity-simulation initiated by EXECl have present- ly been developed only for corn harvesting systems with the following characteristics: 1) The harvest-period labor force must consist of a single man only. i.e.. multi-man. multi— combine systems are not allowed. This single man is. by necessity. responsible for operating the combine. driving the transport sets. and per- forming all other activities required.** 2) The harvest-time handling of corn must be done with option #1 (on-farm high-moisture storage). with option #4 (direct-from-the-field off-farm * EXECl is presently capable of handling planting operations. as will be discussed later. It cannot handle (and event- routines have not been developed for) non-planting. non- harvesting field operations. ** Event codes have been defined. and flow charts for the cor- responding event-routines have been completed for a multi-man. single-combine harvest situation. The development. testing and declaration of an operational status for these routines. however. will have to await the future energies of the author or another investigator. Several of the routines presently operational. including EXECI and a number of specific event- routines. are now capable of handling. or will be applicable to. the multi-man. single-combine harvest situation. With EXECI. though. the multi-man work force must have a common work schedule. i.e.. all men must have the same starting and quitting times. 118 marketing). or with a combination of these two options. i.e.. in-bin layer drying (option #2) and high-temperature drying (option #3). with batch-in-bin. portable batch or continuous flow drying equipment. is not allowed. The procedure used by EXECl to initiate activity-simulation is illustrated in Figure 10. When EXECl was being developed. it was assumed that all user options available with the model input form would in fact be developed and operational at some point in time. The first two tests in EXEC1 are required for one of these user options that is not presently operational: a multi-man work force in which at least one of the men is scheduled to start and/or quit at a different clock-time then the others. i.e.. the active labor force will change at least once be- tween clock-time TNOW and TFIN. With the initial call to EXECl each day TLAST will be less than 999999.0 (set to TNOW in subroutine MYGASP) and file 1 will be empty (number of entries in file 1. NQ(1). will be zero). EXECI then calls subroutine SCHEXC which will schedule (file in events file 1) an EXECl-event to occur each time the active labor force changes. At thggg event times. EXECl will again be called to activate or de- activate one or more men. This portion of the model has not yet been developed. though SCHEXC has been. If on-farm high-moisture storage (option #1)is a corn handling option at harvest-time. as Specified by the model-user. then the model as presently developed will attempt to satisfy this option first. before harvesting any 119 551.}. Egg; Schedule EXECl-events and return Horas): . no. of son in today's labor torso labor I priority fld op Set IO! - sods number of“ ‘0 0’ for ted 1 activity perio- AP I t . I l p ant ng per 9- ne ('quiek—retarn' path) a not yet developed for this partisans- sit tioa AP - 1.2. 3 or S v... ;erlod) AP I 6 (harvest period) yes EAL?“ PLANE plantin:N for triu- non-plant fld op as are “sin: ngn-h.ry..g avg planting (14 op rats E Set NOPfg - gm or I for noniplsnt. mn- tiao hdl‘ lids option Set sets-u no. of off- ara aarkst locations A l s 7 with all eoabines available Set loco: . no. of ooabines yes in-bln layer drying yes high-teap drying no ('quieh-return‘ path) ’M 0 ”9937.0 Kigh-aoisture storass pt is new sat tisflod So. he? C‘l- 999999.0. credit: corn on transport sets this site. disassemble the- H0 GED RDPT - 4 K3110 I 0 Set NOPRI - no. of frastds ave si or oorn storage EéLL.2££_Zl Set K to indicate what action (1 t any) is required m @ ml H’Afi . the first (or next) frastd to use for high-moisture corn storage figkl Goran} east vats silo-tractor used at prev vious store: a site(lr any). then select silo-tractor for this storage sits(if reqo.) Set MK? based on use -s scified garnet selection policy 8st IX? to the only oft-rer- aarket available "gers 10. Executive Subroutine 213:1. 120 designated to haul cor 8st IVER: s the no. of these that now contain sees corn 55%; 185E?“ [ e NOV - no. of transport sets in file 0 a! I.D- 06”.? asltl-eosbins ' system a l onetsrs.hi¢h-soisture s1 04 direct off-tars aarketing 95%; ccglob ‘ at as - start-harvest 0 e a start-harvest field field asset - start-harvest NSECT - start-harvest section in NPLD in-bin layer high-teap section in KPTD drying drying , , éfiapute Elm yield in WSECT yes as > ROVER n s r. the most 7 l critical section in am ’ 7 ‘ Cilia—fiifili . W “’ Assemble more transport at no; 1). the combine sets for corn in file 8 unload pattern required. . and NVEHZ. the no. of I transport sets required {‘ I Setup entity-ID info for today's entities i Setup the start-ef-the-day indicator -- MOT - 10000 + lOOO'NVS.".2 4- lOO'KSILO + woman 0 I 2;”. 00:51; ' ' e unmy events for to- day's entities. set NOON. the no. of such eVents filed A lob. aulti-sehedule sort torso ll on-tara _ {‘ high-so storage [£11.54 A5103; 1 off-lar- marketing Schedule real event(s) based on NACT in-bln‘layer high-temp d ng dr ng ’ * ry ’ glll_5stcnz w Schedule real event“) for transport set unloading Figure 10 (cont'd.) 121 corn to be handled with the other three options. To ”satisfy" this option. all available high-moisture storage specified by the user must be filled, or the kernel moisture of all corn that remains to be harvested must have dropped below the minimum moisture desireable for high-moisture storage. In either case, the fact that this option has been "satisfied” will not be detected until the next initial call to EXECi. i.e.. at the start of a Egg activity-simulation day.* At that time, as will be discussed later, EXECl will set TNOW = 999999.0, as a flag, and a return (to subroutine EVNTS) will be executed without filing any real events. EVNTS returns control to subroutine MYGASP, which examines file 1, and returns Control to the daily simulation loop of Figure 1 if file 1 is empty. If it is not empty ( subroutine SCHEXC may have filed one or more EXECiéevents). then EXECl will again be called, but will detect the flag TLAST (set to TNOW = 999999.0) and take the "quick return" path. The daily simulation loop of Figure 1 is also designed to recog- nize this "quick return" procedure, and branches back to see if an activity-simulation day can be declared for the new harvest-time handling option then in effect (optionZ, 3 or l4). After calling SCHEXC. EXECi sets NOP to the top priority field operation code number for the day (this was originally *The model is designed so that thaparticular handling option in effect at the start of a new activity-simulation day re- mains in effect throughout that day. 122 determined by subroutine GOFLDS), then branches to the appro- priate section based on the value of the current activity period (AP). For activity periods # and 6, NOP is compared with the fld-0p code number for planting and harvesting, res- pectively. If the comparison is not true, a branch is taken to the section reserved for initiating activity-simulation for non-plant. non-harvest field operations. which has not yet been developed. If the top priority job for the day is planting, then subroutine PLANTR is called. PLANTR is a simple continuous- timg planting routine that relinquishes control back to EXECI only after clock-time TFIN is reached, i.e.. only after a full day of planting has been done.* . If the top priority job for the day is harvesting, then EXECI proceeds through the next section of instructions, which are applicable to both single-combine and multi-combine harvest systems. On the first day of the harvest season the NOPTi variables are set (to O or 1) to indicate the feasibility, or * To facilitate the event-oriented activity-simulation techni- ques developed for harvesting, the corn crop had to be planted and brought to "maturity". This simple planting routine was the technique selected for doing this. So even though activity- simulation of non-harvest field operations is not possible with the present model, the model-user is re uired to specify one (only) non-harvest field operation (planting). and to Provide the necessary planting equipment and planting policy specifi- cations requested by the model input form. The field pattern to be used for the planting operation in each field (this is input as part of the field description specifications) must be input as field pattern 2 -- continuous alternating field pattern. i.e.. circular-planted fields (field pattern 1) are not allowed with the present model. 123 lack thereof, of the four basic harvest-time handling options. NOFF. the number of off-farm markets available, is also set if NOPTu is non-zero. and file 7 is loaded (using subroutine LOADCB) with all the combines available for use. NOCOM is set to the number of different combines. The NOPTi variables are then checked. in sequence. to determine the appropriate setting for NOPT, the basic handling option to use in initi- ating today's activity-simulation.* Corn delivery point determinations with EXECi For the two harvest-time handling options developed (options 1 and h), EXECi first considers where the corn that is harvested today should be delivered. For the high-moisture storage option, all corn harvested on a given day is delivered to the same farmstead (storage site) and is placed in the same silo (storage unit)at that farmstead. For the direct-from- the-field off-farm marketing option, the delivery point for each (or all) load of corn will depend on the particular market selection policy specified by the model-user. If high-moisture storage is feasible (NOPTl = 1). and if ii The NQPTi variables are set to zero as the handling options are satisfied. They are re-set (to one), if they are viable options, at the start of each new harvest season. 124 this option has not been satisfied ( X(90) = 1.0), then. on the first day of the harvest season. EXECi sets NOFRM to the number of farmsteads at which high—moisture corn can be stored. From these (NOFRM) farmsteads. NFARM is selected (by subroutine GOFRMI) as the first one to be used. * If NFARM requires the services of a tractor (to operate the silo- filling equipment), then one is selected from the unassigned tractor file (2) by subroutine GOFRM3 and placed in the farm- stead equipment file (11). using subroutine LOADTS. On all subsequent days. subroutine GOFRMZ is called to determine what action, if any. is required concerning the high-moisture storage site. If K = 1 is returned, no action is required. If K = 2 is returned. the silo-filling equipment should be moved from one silo to another. at the present storage site (NFARM), before harvest begins, but after any corn left on transport sets overnight has been unloaded.** * The "selection" portion of subroutine GOFRMI is not pres- ently developed -- an error message will be printed (and an EXIT taken) if NOFRMIa 2 when called. It is anticipated that this selection criteria might involve the total storage capacity at each farmstead. the actual or desired planting sequence of the fields to be stored at each, and/or other factors. "The model-user must specify the number of silos to be filled at each farmstead and the amount of man-time involved in moving the silo-filling equipment. Subroutine GOFRMZ assumes that all silos at a given storage site are of equal size. 125 If K = 3 is returned, all silos at the present storage site (NFARM) have been filled (or will be once the corn then on transport sets has been unloaded). i.e.. all high-moisture storage at this farmstead is (will be) full. If another farm- stead is available for storing high-moisture corn. then the corn harvested today should be delivered to.it -- select a new NFARM, assign a tractor if required, etc. If another one is not available, then the high-moisture storage option has been satisfied. and a "quick return” from EXECI is to be taken -- after crediting any corn then on transport sets to the high-moisture storage site. after disassembling the trans- port sets then assembled, and after returning any farmstead tractors then assigned (in file 11) to the unassigned tractor file (2).* A branch is taken to this point also if N0PT1 a 1, but X(90) = 0.0 at the start of the day, i.e.. the high- moisture storage option is assumed to be "satisfied" (without * The man-time (and farmstead-tractor-time) required to unload transport sets in this situation is assumed to be negligible. i.e.. state-time information for the man, transport sets, and farmstead tractor, if used, is not recorded, and the repair and fuel level attributes of the farmstead tractor are un- changed. The corn transport sets are disassembled at this time since the next handling option to be used (it will be in effect with the next legitimate call to EXECI) may require a different complement of transport vehicles. 126 storing the desired quantity of high-moisture corn) due to the kernel moisture in all unharvested corn now being below that required for safe high-moisture corn storage. If direct-from-the-field off-farm marketing is the handling option for the day (NOPTl = NOPTZ = NOPT3 = 0, NOPTu = 1). then variable MKT is set (or temporarily set) to the off-farm market to be used throughout the day (or for determining the transport system requirements for the day). If there is but one off-farm market location, then it will be used. of course. If NOFF is greater than one. however. then the market selection policy specified by the model - user will be used to set MKT. 0f the seven market selection policies proposed in the input form, only the first 3 are currently operational: Policy 1 -- Random selection for each load of corn. Policy 2 -- Random selection for each harvest day. Policy 3 -- Shortest round-trip time for each load. With policy 1 and 3. MKT is temporarily set to the off-farm market location whose attribute information is stored in the last column of file 11 (all off-farm markets are stored at the back of file 11). 127 gtart-harvest point determyaticns with EXECI Subroutine GOFLDS determined earlier that field work (in this case harvesting) could be done somewherg on the farm today. It is now necessary to determine specifically ghgrg harvest should begin -- so that the combine can be moved there. so that transport sets can be spotted appropri- ately. etc. Before doing this, however, EXECI sets the current value of NOVEH and NVEHI (see Figure 10) by calling subroutine TRSETh. These values will be needed later regardless of the number of combines in use today. A branch is then taken to the appropriate section for the multi-combine situation (not developed) or for the single-combine situation, to carry-out its next function -- selection of the specific field (NFLD) and field section (NSECT) in which harvest will begin today.’ This selection procedure is done by subroutine GOFLDI when handling option (NOPT =) 1 is in effect, or by subroutine GOFLD4 when NOPT = h. GOFLDI makes the selection of NFLD and NSECT by considering fields (and their field sections) in the following sequence: 1) It first considers the last field * For the multi-combine situation. subroutines must be devel- oped to select NFLDi and NSECTi for i = 1. NOCOM. 128 in which the combine worked. if any: 2) It considers next the ”preferred fields" for NFARM. as specified by the model- user. if any -- looking first at those fields currently in- process (in file 10), then at those not currently in-process: 3) It then considers other fields that may be currently in- process (but are not ”preferred fieldsfih and 4) Finally it considers each field in its ”preferred planting sequence", as specified by the model-user. GOFLD4 considers fields in essentially the same sequence, except that a "preferred- fields" list is not provided by the model-user for off-farm markets.* Both routines select the first NFLD-NSECT combi- nation that satisfies the harvest criteria (an unharvested section. kernel moisture in the desired range, and tractable soil conditions). Transport system determinations with EXECI Given the combine, the field and field section in which to begin harvesting, and thecnrn delivery point. the final determination to be made by EXECI is the composition of the corn transport system to be used for the day. Sub- routine SPEEDH (to be discussed later) is called to compute the (combine) "bin yield" in section NSECT. i.e.. the potential harvestable yield in the section minus machine losses (see Figure 10). Subroutine TRSETZ is then called to * With preposed market selection policy #6 a "preferred fields” list will be available. When this option is developed. GOFLD4 should be modified to consider these first before considering the other fields in-process. 129 determine NCRIT. the most critical field section from the standpoint of combine unloading requirements that is likely to be encountered. Assuming all other field sections in 'NFLD have the same bin yield as field section NSECT. field section NCRIT is the one with the longest effective row length (section length minus headlands. if any) that the combine is likely to encounter today. Subroutine TRSET3 is then called to determine the combine unloading pattern (variable MDMP) that will be needed in section NCRIT. and the number of different transport sets (NVEHZ) required to accomodate it. A The basic combine unload patterns defined for STOP- unloading (as opposed to ON-THE-GO unloading) are illustrated in Figure 11. The setting of MDMP(1)* is based on the ratio D = QTNK/QRND. where QTNK is the capacity of the combine's grain tank in cubic feet. and QRND is the (estimated) cubic feet of corn that would be harvested on each round in section NCRIT: If D53 1.00. MDMP(1)= 1 is set. The combine can make at least one full round (2 harvest passes through the field). so unloading is needed only at one end of the field. If 1.0>D3 0.50. MDMPU) = 2 is set. The combine can make one full pass. but not a full round. so unloading is needed at both ends of the field (requiring 2 transport vehicles). or mid-way through the field (re- quiring only 1 transport vehicle). * Variable MDMP is dimensioned to 5 to accomodate the multi- combine situation. i.e.. up to 5 different combines. .msseeeacs.aoan you..:uoepem meaeeoacs ecseaoo .HH enemas .eaeam one saucers nausea ;\n .uaoau esp .hnso candy ogv use ;\a can as weapons smacks» assuas coupons we use one as newness noaoasob puoaussse no Anvoaoano> phonnssne An Auvoaowzo> vuonnssna As 130 Us 1.1 He 11 Ila a na ._ i ,_ E Il- n u Aevmxnx N u assess: a a “Hyman: 131 If 0.5>D?-’0.25. MDMP(1) = 3 is set. The combine can make half a pass. but not a full pass. so unloading is needed at both ends of the field and in the middle (requiring 3 transport vehicles). or at the 1/4 and 3/4 points through the field (requiring only 2 transport vehicles). If D«ape< nuances: use mean-esnmm :uou you seesaw-m us«n=oenou use)“ .«u shaman an“. puo>hmnupusva eunuuushouc« axe: onu oeuunuo ow He>sau snapsou on umnu xus» sass» Hausa nose .vou uuonucsu» a can“ convened ensues- unmask->0 souvsooa e shown hounfilhfl Chou 02d 0? H0>¢hv .CleOU us madcap» .auusnon .wuauno>anz scannoo couuaeoa vaoauncu so: a cu vamoa >Lo>unou s scan cannon can .pm scans: .ou He>sau pom uaoaucahh «anon uao>asnnua¢aa we. «panacea» uzmucus>o aua op Hs>uuu scansou an“ op coausooa luau-nus :s scan xuas ao>suv Lo\vcs nauseous: uo\ucs enema m sea“ ~o>uau use unoauzaua “annuossv we unacoauuuoa caeuuona ho\u:d toa>hom ”sauna“ on» us scapnoo sound-on ao\o:c som>aom usosausae sandman 0a“. o>o= V essences “a savanna vacuums-u s ooa>hom vsoHCD 148 the type of activity or activities for which events are to be scheduled. while the arrows represent alternative sequences in which event scheduling may proceed. In some cases it was found desireable to have an event routine scheduleoonly the very next event to occur. In others. an event routine may schedule a whole series of events. Activity State Flow Charts Activity state flow charts were used as an aid in the event scheduling development. Given the activity states in which entities can exist (see Table 3). an activity state flow chart is helpful in visualizing the proper sequence of activities (activity states). in identifying events. and in determining event routine requirements such as what action should be taken by the event routine with regard to changing activity states. in calculating the material levels or the fixation of entities. in scheduling additional events. etc. Figure 13 illustrates two simple activity state flow charts for a series of activities involving a single entity (13a.) and for one involving two entities (13b.). The arrows desi- gnate activities and the nodes designate events. to which event code numbers have been assigned. As was noted previously. repair activities may occur only when entities are in certain ”operate” states. For the combine this is state 4. on-row operation. As can be seen in Figure 13s.. the event routine which processes event 12. the conclusion of the repair or adjustment activity. must return 149 .mpueno roam opepm spa>apo< .Haasm .ns enemas .Amspumoass:moamvapnopsoo psommso m.xsmp spasm exp mo Has nae: smo psnp pom meAmcsmp s op osupsoo s soup nohmcmmp choc an Aaasu:socv osppsoo scum “Hasm:co:v uo>pmc m psonpas mapppss shoe o>pooom mo>pmu m psonpps mapppme _s AHV . pom _ ®A m H phones—sup m opspn a opmpm m opspm > . soap .smoo Awspsoamsp smoov pcpoa pmo>mmn pom puoamcmup on Awspsoamsp smoov soppmmeao :pmspm pun: esp op pm acmup soapsmeao som::o esp op o>os shoe monmssup esp op o>os som::o A @A flee. ®A $9 as... : opspm m opspm n opmpm n opspm : opspm .caopm esp we use map pm sump Hesse: use coprSMAopC« scansoo Am campy esp mpcospms cm soppmMoao no use esp soppmMoao no app on soapsnoao som::o pm wsasmsp 309::0 mom veaaopm som:so N a opspm opspm # opspm w opspm : opspm 150 the combine to state 4.* Another important function of this particular event routine is to reset a value for the combine repair attribuuathat became zero. thenay indicating the need for the repair activity just concluded. Thus. in addition to the event code. the event time. and the time at which the combine last changed states. an entry in file 1 for event ~code 12 must also have one attribute (one of the ATTi cells of Figure 9) which is the accumulated hours of use until the next repair of this type will be needed. Other event routine requirements can be determined by studying Figure 13. These include: 1. Event routines for events 11. 14 and 36 should adjust the repair and EPM attribute values of the combine. They should also update the corn level and moisture content in the grain tank. and the acres harvested in this field (file 10) and for this field operation (file 9). 2. Event routines for events 11. 14. 36. 18 and 19 should adjust the fuel level in the combine fuel tank. and update the combine's current location. 3. Event routines for events 18 and 21 should change_ the activity state of both the combine and the transport set involved. and the event routine for event 21 should also adjust the corn level and moisture content of the combine (reduce the level) and of the transport set (increase the level by an equal amount). The event routine for event 21 must also recognize the situ- ation in which the transport set cannot hold all of the grain tank's current contents. In this case. rather than the trans- port set being placed in dummy-delay and the combine moving back to the corn to continue harvest. the combine must be *An operate interruption for a transport set may occur when the unit is in state 1 (out-of-field travel) or state 2 (in- field travel). 151 placed in dummy-delay. the operator transferred to the transport set. and a series of events scheduled to move the transport set to the corn delivery point and then back to the field. This is illustrated in Figure 14. With the aid of activity state flow charts. 56 real events (event codes 5 through 60) were identified for the one-man and multi-man (one combine) situations in which corn could be stored on-farm in high-moisture storage structures or marketed off-farm at harvest. Of these. it was determined that 29 real events. and event routines to process them. were required for the one-man situation (see Table 6). The event routines designated for specific events in Table 6 fall into on: of three categories: 1) the routine is required only for the one-man situation and presently operational: 2) the rou- tine is required for both the one-man and multi-man situations but is presently operational for only the one-man situation. or 3) the routine is required for both situations and is presently operational for both. The file 1 entry requirements for the events listed in Table 6 are presented in Appendix E. Computing Real Event Attribute values The routines that schedule real events are designed to compute certain types of floating-point attribute values:* 1. In-field coordinates. The new x.y-position which 33.322353liogii‘ifiisairi";.2?§“.§§23°%y°i.:2d§:"*' codes onl (1-6 for farmsteads. 11-16 for off-farm locations). ‘'In addition to assigning all necessary fixed-point attribute values. i.e.. the event code. the required entity-ID infor- mation. and the current mode of operation indicator -- see Figure 9 and Appendix E. .AnopoAm casuscovpom phoneme...“ < .3: pg 9.33.25 1249 54.6 no.“ p.558 scam epapm 5:33 .3 933m spas eusnops ouspaaos:£mp£ s ps usoacs Ampassu a aaasu:cosu sacs sacs ue>puv s pso epnpa ao>uuv a psozpps wrapper e>acoom :npas snapper sacs esos “Adsuncocv o>flouou me>auu s pnonpps ncapwns zpassv “pushy coppuaon ceppsuoa 152 pun 1: .Aeau sec s posses o~o«u:uo:pso paonnuu a spspn susuuuuo op o>oe : epnpe m epspe b .. cs pa seeds: p .. + . : spspa spspa .. . 3 I . . “u n epspa x _ . 2 : . . .. : . . 2 2 . _ _. n. u . .. . 2 _ soap hepnuuao mopnuono sod» Chou OrJDEOU acrylic". CLOU _ 3 _ : u z n _ _ x u. _ . . . .. I . — —. ._ - _ .. .. _ . 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Activity times. The time of ammo of an event. TNEW. is the current clocktime. TNOW. plus the time required by the entity(s) involved to perform the activity. Ta (TNEW - TNOW + Ta). 3. Harvested-crop values. The adjustments to be made in the grain tank attributes of the combine (bushels. cubic feet. moisture content) at the conclusion of a harvest pass will depend on the existing attributes of the crop in the particular field section (potent- ial harvestable yield. current moisture content. amount of stalk lodging). on certain attributes of the combine (on-row operating speed). and on the interface between these two (machine losses). The following discussion details the computational techniques employed. In-field coordinates for combine harvestiag With normal pattern harvesting (continuous alternating field pattern). the combine moves (simulated movement) as indicated by the arrows in Figure 15. when harvest is proceed- ing away from the field origin side of the field. This move- ment is interrupted only by the need for repairs or adjustments. or by the need to unload the grain tank. In the former case. the combine is stopped in-place. and then proceeds from there at the conclusion of the repair activity. In the latter case. the combine moves to the appropriate transport set. unloads the grain tank. then moves back to the corn to continue harvest- ing.’ The point to which the combine moves when it moves (back) to the corn to continue harvesting is called a "start-harvest” point. *The x.y-coordinates of the combine are assumed to coincide with the x.y coordinates of the transport set during the grain transfer activity. 155 .msopnhm mappno>msx sax:oso mom mpsoso>oz use osopppmom hpppsm oaassm “gasps mmspvossacmon moroa Huaavmxax pom pmonmsmmp x); nnuu emInsane—ac opopp onp no esp. sampuoueaouu esp soup ants mspoesooma poo>mss .smoo oopmo>hsnss 533 communes .I ‘ ‘ « ‘ n—s» a ml Sosa. pm pom pmoaossmp «A H Ema. pom phonmsmhp U ml Same: ~* pom pmvossup Alul C. compo... 3.3 so oesopuse Aapmpo suspvosmfloso: moans ’(\ a C C .ns enemas \I 2853 3.3 IT 2320 II\ macaw a: lull! 156 The x. y-coordinates. with respect to the field origin. of the next start-harvest point. and the field section number in which it resides). are required at the start of the day (the initial start-harvest point). when the combine turns at the ends of the field. and for the "return" event following grain tank unloading. Two subroutines. MVOVER and WISE. were developed to assist with the computation of x.y-coordi- nates of this type. Subroutine MVOVER (NF. NL. NN. XN. MP. D. ND. XD. JJ) is used for x-coordinates in a field in which NP and NL are the first and last sections. and x-coordinate XN is known to reside in section NN. If it is desired to move over a distance D (rods) from IN. then MVOVER returns XD = XN + D. for a move to the right (MP = 2). or XD = XN-D. for a move to the left (MP = 3). and ND = the section number in which XD resides. If XN i D is within the field boundaries. then JJ = 1 is re- turned. Otherwise. MVOVER returns JJ = 2. XD = the x-coordi- nate to the appropriate field boundary. and ND 8 NL (for MP = 2) or NF (for MP = 3). In determining the x-coordinate of the initial start- harvest point for the day. one sets NF. NL. NN. XN and MP based on the attribute information stored with the field to be harvested (in file 10).* Then before calling MVOVER. D * The setting of XN is based on D1 (see Figure 15 and file 10 in Appendix B). the horizontal distance between the appropr- iate field boundary and the nearest edge of an area of unharvested corn. D1. and its corresponding field section number. is updated as needed by the routines that process harvesting events. 15? is defined as one-half the cornhead width. The returned value of XD is the desired x-coordinate. In determining a new x-coordinate for turning at the end of the field. )uaand NN are based on the combine's existing location prior to the turn. and D is defined as the whole cornhead width. Subroutine WISE (NF. ND. XD. Y1. Y2. Y3. Yh) is used for y-coordinates (y's) in a field in which NF is the first section. Given the x-coordinate XD of a line which resides in section ND of that field. WISE returns y-coordinates for Y1 - the lower field boundary Y2 - the lower edge of the unharvested corn. i.e.. Y1 plus the headland width Y3 - the upper edge of the unharvested corn Y# - the upper field boundary. Note that if no turn rows were planted. which is a require- ment with the model in its present stage of development. then Y1 = Y2 and Y3 = Y“. Note also that subroutine WISE is much more useful for irregularly shaped fields than for rectangular fields like the one illustrated in Figure 15. The initial start-harvest point for the day is always at the lower end of the field. e.g.. the combine in Figure 15 could be positioned at the initial start-harvest point for the day if some harvesting had already been done in this field. The x.y-coordinates of this point would be (XD.Y2). as found by using subroutines MVOVER and WISE as indicated.* * Subroutine GOFLDZ is called at the start of each activity- simulation day to. among other things. compute the x.y co- ordinates of the initial start-harvest point for the day. 158 If the combine unload pattern for the day were MDMP(1) a 2 (see Figure 15). then the initial harvest pass by the combine would be from point (XD. Y2) to point (XD. Y'). where Y' = Y2 +(Y2 + Y3)/2. Following grain tank unloading into the transport set. the combine would then harvest from point (XD. Y'). to point (XD. Y3) at the upper end of the field. then return (harvest back) to the midpoint of the field for the next grain tank unloading activity. If the combine un- load pattern for the day were MDMP(1) = 3 (Figure 15). the first grain tank unloading. into transport set #1. would occur after the combine had harvested from point (XD. Y2) to point (XD. Y'). where Y' 8 Y2 + (Y2 + Y3)/h. while the second unloading. into transport set #2. would occur after the combine had harvested from point (XD. Y') to point (XD.Y" ). where Y" = Y2 + 3(Y2 + Y3)/h. In-field coordinates for transport sets When a transport set is to be positioned in a field. it is always done so in relation to the combine's current x-co- ordinate. or the next x-coordinate along which the combine will be harvesting. if it is not harvesting at the time the positioning event is being scheduled. The x.y-coordinates of transport sets are computed. with the aid of subroutines MVOVER and WISE. as follows. where XX is the x-coordinate of the current or next combine harvest pass. and Y1. Y2 and Y3 159 are as defined in the preceeding discussion:* 1. MDMP(1) = 1. One transport set required. one extra transport set may be used for multi-man systems. Define position 1 at 2 rods (position 2 at 4 rods) beyond line XX. 1/2 rod above Y1 at the corresponding x-coordinate(s). Beyond line XX means to the right of XX for MP = 2 (harvest proceeding away from the field origin side of the field). or to the left of XX for Mf’= 3. If 2 rods beyond XX is outside the field. then reset position 1 at 1/2 rod from the edge (side) of the field. 1 rod above Y1. If 4 rods beyond XX is outside the field. then reset position 2 at 1/2 rod from the edge of the field. 1/2 rod above Y1. 2. MDMP(1) = 2. One transport set required. one extra transport set may be used for multi-man systems. Define position 1 at 1 rod (position 2 at 2 rods) behind line XX. midway through the field at Y2 + (Y2 + Y3)/2. If 2 rods behind XX is outside the field. but 1 rod is not. then reset the x-coordinate of position 2 only. at 1/2 rod from the edge (side) of the field. If 1 rod behind XX is outside the field. then reset both positions at 1/2 rod from the edge of the field. the first 1/2 rod above. the second 1/2 rod be- low the midpoint. 3. MDMP(1) = 3. Two transport sets required. one extra transport set may be used for multi-man systems. Define all positions at 1 rod behind line XX. the third position (extra unit) 172 rod above Y1. the second position l/h-way through the field at Y2 + (Y2 + Y3)/h, and the first posi- tion 3/h-way through the field at Y2 + 3(Y2 + Y3)/h. If 1 rod behind XX is outside the field. then reset the x-coordinate of all positions at l/h rod from the edge (side)of the field. * Subroutine GOFLD3 is designed to compute. and return to the calling program. up to three x.y-coordinates as indicated. A new in-field position is computed each time a transport set unloads at an out-of-field delivery point. Transport set positions are set somewhat differently by GOFLD3 for on- the-go combine unloading and when a field with turn rows has not yet been opened-up. 160 Activity times for daily maintenance and refueling Daily maintenance and refueling of tractors. combines and trucks was assumed to require 10 minutes plus refueling time at a rate of 250 gallons per hour. The need for this type of service activity. as was discussed previously. is deter- mined at the start of each activity-simulation day by com- paring the current fuel level with the fuel tank capacity of the entity.* A difference of one gallon or more indicates a need for daily servicing. If an EPM job is also needed. then the time required to perform it is added to the daily servicing time. Activity times for on-farm transport set unloading On-farm transport set unloading with the present model refers to unloading at a high-moisture storage site (a silo). The total time required is computed as‘Ta = Tsk + (Q/TR). where Tsk is the setup and knockdown time (hours per load) specified by the model-user. TR is the actual corn transfer rate (bushels per hour) specified by the model-user. and Q is the load size (bushels). Unloading activites of this type may be interrupted only by the need to repair a tractor used to operate silo-filling equipment. if one is used -- it is assumed that the silo being filled can hold all of the current contents of the transport set. * With the model in its present stage of development this Acheck is made only at the start of the day. i.e.. a fuel level checking procedure throughout the day has not been incorporated_into the event routines. Consequently. cer- tain entities may have a negative "current fuel level" at the end of an activity-simulation day. 161 Activity times for off-farm transport set unloading The time needed to unload transport sets at off-farm markets requires a simple "look-up" technique with the present model. One first determines the clock-time at which the transport set will arrive at the off-farm location. then selects the total unload time from the appropriate column tin file 11 if arrival is before 9:00 a.m.. 9:00 - 11:30 a.m.. 11:30 a.m. - 1:30 p.m.. 1:30 - #300 p.m. or after 4:00 p.m. These "total unload times" are supplied by the model-user and should reflect the time required for weigh-in. weigh-out. sampling. waiting in line. actual unloading. and all other relavent activities at the particular site. Activity times for grain_tank unloading The time required‘matransfer corn from the combine to a transport set depends on the quantity of corn transferred and the transfer rate. The quantity of corn to be transferred for a given transfer activity is computed as min(Qc. Qt). where QC is the current grain tank contents (cubic feet). and Qt is the unused corn transport capacity (cubic feet) of the particular transport set. The number of bushels to be transferred (equivalent No. 2 bushels) is computed using the kernel moisture-volume relationship noted previously. “Overloading” of transport sets is not permitted. even if only a bushel or two of corn remains in the combine grain tank. With the one-man system. the combine is not allowed to continue harvesting until the grain tank has been emptied. 162 The transfer rate for a particular combine is computed as: TR = 36 * HP + 360. where TR is the transfer rate (cubic feet per hour). and HP is the rated engine horsepower of the combine. This relationship assumes that most combines are designed to unload their standard—size grain tank in about 1.5 minutes. and that the unloading unit is a volume measuring device. It was developed using standard grain tank sizes and engine horsepowers of combines commercially available in 1967. Activity times for grain tank unloading (in hours) is computed as min(Qc.Qt)/TR. Activity times for transport set travel In the real world transport sets may have occasion to travel between two in-field points in the same field. two in-fiold_points in different fields. an in-field point and and out-of-field point. or two out-of-field points.* In addition. the travel characteristics. especially speed. of the two types of transport sets. truck-powered and tractor- powered. are quite different. To simplify activity time calculations within the event routines. a group of four subroutines were developed: TRAVEL to compute and return the minimum travel time required. DISTI to compute in-field * All of these different types of travel are not possible with the restrictions and limitations presently imposed on the model. Travel between two in-field points in the same field. for instance. would be needed for a multi-man system with on- the-go combine unloading. but is not needed for a one-man system. i.e.. the combine always moves to the transport set for unloading. rather than vice versa. with the event routines presently developed for the one-man system. 163 distances. DISTO to lookup out-of-field distances. and SPEEDT to lookup or compute travel speeds. Subroutine TRAVEL (KCOL. LTO. XTO. YTO. TVT. NSET. QSET) computes and returns the minimym travel time required (TVT in hours) for the transport set in column KCOL of file 8 to move from its present location to a new location LTO. LTO may be off-farm locations 11 - 16 (coded 211 - 216). farmsteads 1 - 6 (coded 101 - 106). or fields 1 - 30. In the latter case. (XTO. YTO) must define the x.y-coordinates of the in-field point to which the transport set is to be moved. The term "minimum” refers to the minimum of the travel times for the various paths which the transport set may follow to get from one point to another. When at least one of the two points is within a field. then two or more travel paths may be possible. Figure 16 illustrates this: Fields 1 and 2 are adjoining fields with a secondary entry point‘ between them. and each has one principal entry point onto the same road.” In moving from its present location in field 1 to the desired location in field 2. the transport set may follow path 1 (a combination of in-field and out-of- field travel) or path 2 (consisting wholly of in-field travel).' * See Appendix C for a discussion of principal and secondary field entry points. 16b Field 1 ‘ Field 2 current -1r-= a principal field transport set entry point location ..4)... a secondary field : entry point )---h I, \‘ I “ Path 2 Path 1” \ I \ 1’ \\ desired ,’ ":-.-Q9 transport set I; ,a' location -h—-Ot 0" ‘ ------- t ------- ’ road or farm lane Figure 16. Alternative Travel Paths Between Two Points in Different Fields. Subroutine TRAVEL is designed to explore a number of alternative travel paths. and return the minimum time re- quired. when one or both of the two points are in a field.“ When travel is between an in-field point (in field A) and a farmstead or off-farm location (some out-of-field travel gill be required). subroutine TRAVEL considers those travel paths * In the real world the driver of the transport set will de- cide which path to follow based on his knowledge of the alternative routes. the terrain. existing surface condit- ions. and the capabilities of the transport set given its existing state of loading. i.e.. empty. partially loaded or fully loaded. 165 leading tova roadway through the principal field entry points of 1) field A. 2) B-type fields. those that may be entered from field A through a common secondary field entry point. and 3) C-type fields. those that may be entered from B-type fields through common secondary field entry points. When travel is between two in-field points* in different fields. subroutine TRAVEL considers pptegf:field travel paths between all principal field entry points found by the above procedure (for both fields). and by those in-field travel paths that use no more than two secondary field entry points. Subroutines DISTI. DISTO and SPEEDT are subordinate to TRAVEL. Subroutine DISTI (N. XA. YA. XB. YB. D. NSET. QSET) computes and returns the distance (D) between point A (XA.YA) and point B (XB.YB) within a given field (N). The points may be anywhere within the field. including principal and secondary entry points on the field boundary. In its present (simplified) version. DISTI assumes that if the line con- necting point A and B is the hypotnuse of a right triangle. .then travel will be along the legs of the right triangle. i.e.. vertical and horizontal travel with a right-angle turn.* * DISTI computes D as ABS(XA - XB) + ABS (YA - YB). This method can result in significant travel distance error. especially in irregular shaped fields where the upper and lower field boundaries are not horizontal and/or parallel. Also. application of this driving technique is unrealistic in many real world situations (irregular shaped fields) as it could result in the transport set traveling across un- harvested areas of corn rather than around them. 166 Subroutine DISTO (NA. NB. C. D. E) looks-up and returns the paved road distance (0). the gravel road distance (D) and the farm lane distance (E) that will be encountered when traveling between two out-of-field points (NA and NB). These points may be off-farm locations 11 - 16 (coded 211 - 216). farmsteads 1 - 6 (coded 101 - 106). or principal field entry points 1 - N. where N is the total number of principal field entry points on the farm. The various types of distances. taken from the model-user's specially coded farm map (see Appendix A). were stored in the X-array by initialization subroutine FARMZ. which also assigned code numbers to the various principal field entry points. Given the in-field and/or out-of-field distances of a particular travel path. the travel time can be computed di- rectly if the travel speed is known. Subroutine SPEEDT (KCOL. R. S. F. G. H. NSET. QSET) was developed for this purpose. SPEEDT determines the type of transport set in GASP column KCOL. and its current loading. then returns the maximum (average) speed that could be expected if the unit were traveling on a paved road (S). and the decimal fraction of S that could be expected if it were traveling on a gravel road (F). on a farm lane (G). or from one point to another within a field (H) -- see Table 7.’ * Actually. F. G and H are returned as1fls inverse of the decimal fraction of S. which may be interpreted as the miles of travel at S that would be equivalent (in time required) to one mile of travel on the other type of surface at the lower speed. List variable R is required only when subroutine SPEEDT is used for combine travel. as discussed later. 167 Table 7. Travel Speeds for Various Mobile Entities. Fraction of S Possible on Other Surfaces Type of Equipment Paved Road Gravel Farm In or Transport Set Speed Range(S) Roads Lanes Fields (mph) Tractors with implements 19 0.90 0.75 0.50* Self-propelled combines 12 - 16 1.00 0.70 0.50* Tractors with wagons 16 - 19 0.90 0.70 0.45 Trucks 35 - 50 0.85 0.65 0.h5 * Applicable only to non-operate travel. i.e.. does not apply to on-row operation in the field. The maximum (average) speed actually returned by SPEEDT is somewhere in the paved road speed range shown in Table 7. depending on the current loading situation. and for tractor powered units. the tractor size. For trucks the speed is come puted'as. 50-15(QHAUL/QMAX). where QHAUL is the actual bushels of corn (or pounds of production supplies) being hauled. and QMAX is the maximum bushels of corn (or pounds of production) supplies that could be hauled. For tractor-powered units. the Speed is computed as: 19-(19-SS)(QHAUL/QMAX). where SS is com- puted as min(max(0.286HP+1h.43.16).18) and HP is the rated PTO horsepower of the tractor.“ * This relationship was developed using several different sized tractors that were being marketed in the 0.8. in 1970. and their advertised speeds for the fastest trans- mission setting (gear n) and the next slowest setting (gear n-1). 168 Activity times for combine travel Activity times for combine travel (non-operate travel) are computed or set in different ways depending on the type of travel involved. Activity times for all travel required before harvesting activities actually begin. and after they are concluded on a given day. are computed by subroutine TRAVEL and its subordinates DISTI. DISTO and SPEEDT. Subroutine SPEEDT returns a maximum (average) speed for paved road travel in the range shown in Table 7 based on the row width and size of the cornhead being used: 12. 1“ or 16 miles per hour for 2-row. 3- row or h-row and larger "wide row" cornheads (row widths greater than 30 inches): 12. 13. 15.5 or 16 mph for 3-row. H-row. 6-row or 8-row and larger "narrow row" cornheads (row widths of 30 inches or less).* During normal-pattern harvesting. the travel times associated with unloading the contents of the grain tank onto a transport set (travel to the unit. then back to the corn) are based on a 3 mph travel speed. and a travel distance as computed by subroutine DISTI. All such travel activities are assumed to require a minimum of 15 seconds of clocktime. Combine turning at the ends of the field is * These speeds were developed using the advertised speed ranges of different sized combines marketed in the U.S. by several manufacturers in 1970. 169 assumed to require 30 seconds for the continuous alternating field pattern. Combine operating times and harvested-crop values The activity time required for a given combine harvest pass depends on the on-row operating speed of the combine and the length of the harvest pass.* The amount of corn to be added to the grain tank at the conclusion of a harvest pass (at the event time) depends on the area covered (in acres) and the "grain tank yield" (in bushels per acre). where ”grain tank yield" is the potential harvestable yield of the particular field section in which the harvest pass is being made (as computed by subroutine YIELDZ at the matu- rity date of the corn in that section) minus preharvest losses and machine losses. Subroutine SPEEDH (NCODE. NSECT. NDIR) was developed to assist with event-attribute computations of this type. When called. SPEEDH computes (or sets) values for a number of variables related to combine NCODE (271 - 275). harvesting * The length of a particular harvest pass can be computed as illustrated in the preceeding discussion of in-field coordinates. The area harvested is proportional to this length and the width of the cornhead. 170 in field section NSECT (1 - 100). and traveling in direction NDIR (1 = +y direction. 2 = -y direction).* These include: 1. Kernel moisture (decimal. wet basis) of the corn in field NSECT. 2. Amount of stalk lodging (decimal) present in section NSECT. 3. Potential harvestable yield (bushels per acre) in section NSECT. h. On-row combine operating speed (mph) for normal pattern harvesting. 5. On-row combine operating speed (mph) applicable during on-the-go grain tank unloading activities only. 6. Preharvest loss (bushels per acre). 7. Gathering loss component (bushels per acre) of machine loss. 8. Cylinder loss component (bushels per acre) of machine loss. 9. Separation loss component (bushels per acre) of machine loss. 10. Grain tank yield (bushels per acre). * SPEEDH. and the model input form. was originally developed to accommodate up to 5 different self-propelled combines. The NDIR list variable simply desi nates one of two storage locations (for the values computed? in the X-array. This feature. the capability of having two sets of values stored at any given time. was designed to minimize the need for re- computation of values when a "land" pattern of some type is specified by the model-user for harvesting. In that case. alternate harvest passes by the combine might be in different field sections (with different yield. moisture and lodging characteristics). The feature is also useful when a given harvest pass involves the gathering of corn from two ad- jacent field sections. 171 Preharvest loss was modeled as a function of stalk lodging only. cylinder and separation losses as a function of kernel moisture. and gathering loss as a function of both stalk lodging and ground speed. The specific loss relationships used. along with combine power-requirement relationships. were those developed by Parsons 33. pl. (1971)0’ In setting the normal on-row operating speed. SPEEDH is designed to recognize three alternative speed-setting policies that can be specified by the model-user. A tent- ative speed is initially set as follows: 1. Constant speed policy. SPEEDH sets the tentative speed to a value specified by the model-user. 2. Variable speed policy based on power requirements. SPEEDH increases the speed by increments until the total power requirements are within * 0.5 hp of 0.95AHP. where AHP is the rated engine horsepower of the combine. 3. Variable speed policy based on gathering loss. SPEEDH increases the speed by increments until a further increase would cause the actual (computed) gathering loss to exceed an ”acceptable” gathering loss value. with the existing amount of stalk lodghg in this field section. as computed from model-user input values. * The power requirements for harvesting were divided into three main components: 1) That required to propel the combine (ground drive hp) which was modeled as a function of ground speed. for a given combine: 2) That required to gather the corn (cornhead hp) which was modeled as a function of feed rate: and 3) That required to process the corn (cylinder and separator hp) which was also modeled as a function of feed rate. Feed rate was defined as the rate of material delivered to the cylinder. which is a function if speed. cornhead width. harvestable yield and gathering oss. For (f1: arr. ten men red spe hp SP1 rel If qu pr ur 5} 172 For policy No. 2. this tentative speed setting is also the (final) on-row operating speed stored in the appropriate X- array location.‘ For policies No. 1 and 3. however. the tentative speed is used to compute the total power require- ments. If they exceed 0.95AHP. then the tentative speed is reduced by increments to arrive at a (final) on-row operating speed with acceptable power requirements. i.e.. within 1 0.5 hp of 0.95AHP. The Speed applicable to on-the-go unloading is set by SPEEDH even though this may not be a viable operating pro- cedure for the system under study. To do so. the extra power required to convey the corn from the grain tank is computed. If this extra increment of power causes the total power re- quirement to exceed 0.95AHP. then the on-row operating speed previously set is adjusted downward. Otherwise. the on-the-go unloading speed is set equal to the normal on-row operating speed. With all three ”normal" speed policies. SPEEDH bypasses the tentative speed-setting procedures outlined above if the amount of stalk lodging present in the field section exceeds a "severe-lodging” limit specified by the model-user. In this case. the on-row speed is set to a (usually lower-than- normal) value specified by the model-user. This speed-setting option was originally planned for use with a harvesting simu- lation technique in which the combine would be allowed to * Where it is available to event routines for computing the activity time of a particular harvest pass. 173 move only short on-row distances before being interrupted by a minor repair or adjustment activity. thereby simulating the frequent cornhead plugging problems associated with harvesting severely lodged corn. which is a common mode of Operation in the real world under these conditions. This feature. however. has not been developed. Machine losses. and grain tank yield. are computed by SPEEDH before or during the speed-setting procedures as re- quired. Subroutine SPEEDH has a ”quick-return" capability to avoid unnecessary. duplicate computations if the kernel moisture. harvestable yield and stalk lodging of section NSECT are within certain tolerances of what they were the last time computations were made.’ Sample output of event sequencing Subroutine PRINT4 was developed. to print an event log for certain specified fields and/or on certain days. The event log lists the events that occur (event code and des- cription). the time of occurance (clock-time). and the activity time of the activity just concluded. Figure 17 presents sample event logs. * Values of the 10 variables previously listed remain un- changed in the x-array locations where they are available to event routines for defining the required event attributes. 17h ...g.-..-..--.--.-0.....0...-.--.---.---.q-...D..uovg...poz: EEOCK'EVENT_THIS_EVENT"5IGNIES”EV670?_VQIT DURA710V'OF 71m: coo: ACTIVITIES [OR WHAT ENTITIES THIS ncYIVITv ........-...--------.......-....--...--..-.q’-.--..-.-...-.. HRS w1N~ SEC 7.00 8 {RAMS SET l'lNITIAL SPOTTING IN THE FIELD....C'OOC .9....Q_Q-._._'l..ne —,:fiT——-y-—EOM§TVE“271-1NITIKI—z55fTIN°'I" O O 1&_ THE FIELD 10 BEGIN HeRVEST...... o o‘ 36 7.07 14 COMBIVE 271-HABVFSTIMG~ON-Row..... 0 3‘ as "7763"“T3"‘CUMETV€‘27I‘TDRNIwe £7 YHE END}... 0 o~ so 7.1e 36 COMBINE 271-HARVESTING ON-ROW..o., o 3‘ as 7.16 18 COMBINE 271'IRAVELITh.A TRANs' f SEi—TO'WNLUADOOQQOl00000.0...O.. 0 O 15 In‘NS SEW I'DELAYeeO eeOOeeegeeQQ. o 5 l7 7.16 21 COMBIVE 271-COHN YRAMSFER ture. . 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O o 16 13.51 55 TRANS set i-ngonojna cone ATYA HIGH MC SILO‘OOeeO.eeeoeeeeeeO,. 0 6 35 __.-.-.--.------.-O-n.0C-D-Op...QQDQ-OO.OOO-CDCQQDCUC..D..O IRANSPORT SETS IDENTIFIED ABOVE!WERE CONFUSED 0' YHESE ENTITIES -' 1 s 341 0 0 a) Combine Unload Pattern 1. On-Farm Storage Option. Figure 17. Sample Event Scheduling. 175 ...O..-..-..O.--.-.-.--.........I...-:’tt.......-.’.:..... ICDCK‘EVENT’THIS'EVENY SIGNALS END OF HHIT OURA710‘:OP TIME coo: ACYIVXYIES {on euAr cNtints THIS ACVIVIVV he. ulu Ste 7.13 e teens 56? 1-UN'OAD1NA cone A1 A ”15* “C SILOOOOeeOeeeeeeeeLL ‘V'Tt"‘3“YHAvs SET 1-1V111AL:500111N0 1N ' . 7H7 FIELDeeeeee..e..eee..e..eeg. 0 .‘ ‘3 7.A7 15 congywc 711v>£nv1c1Ne.......Ll,. o “177t“'v—‘Coug1ve ?71-IN171AL coorr1uc 1N , :ur r1510 10 sisru unnvesf...o.. 0 1‘ 12 1.5e 36 cowaxvc 211-NARVESYIua ON-ROa o ' ' “7755‘_IU_—C0“BIVE 271-IRAVEL17n A IRAN: O SC? 70 UNLUA000.e-..e00e::..e0.. . ’31 TR‘QS SET ‘.UELA'..O' .000. ' "7"53 2! Cbflsxif 271'CORN fRAusFER 1u10., TRAVS SE? 10.0.0QOQOOIOOQO...... . .' ,‘ 7.56 19 cowervc 271-IRAVEL'BICK To fut €091 To 8601" Han: udnvesrinc... o 0 152 7.62 1. COMBIVE ?71-NARVE511uc 0N-n0v..:.. 0 3 27' 7.63 13 coneyvc 211-tunnxvo :1 1H: 53 "7’KU“36“tOH8:VE PIT-HAR9E511~3 ON-ROu..... 0 3 17 7.50 18 coug1vc 211-12AVEL:th A IRAN: SE? 79 UNLU.0000.012.0_0-.’04....L a o is. YR‘VS— SET_ ‘-UEL‘Y....O.I.......... 0 ’ 5" 7.71 21 c0v81VE 271'CORN rnAuerR luro TQAVS SET 10000.00.e000eee.eein. 0 ! 1A "1—7r—‘rq——tUH§1VE“27f=T§AVEETE'cx to THE' con» to stain Man: u.nvcsf:nc... e e 15 7.77 1‘ COHBIVE_27IZNIRV5511vgypfl-90i..... 0 3 le “‘7778“T3“CUFB1VE 271-YURNfVc .1 1H: £u0.:.. o e 30 I ‘1:711"1V"tUH91VE”21131RAVEL:sxcx-to 7u¢e conv to BEGIN "one HARVEsfiVGeg. e e. 1! 1t.13 ll CONBIVE 271.005 7: BOEAKoowy. oa‘VEEo row HACuiNe ADJustueuf TEnwvatg UN-ROJ Htev5511fle..e.. 0 0 53 11,35 12 couggvc 211-H55513_Oe Ap_JUSYv£NV RESJME on-nou HAnvrsrxnc.....-.. 0 13 37 ....° 1. couggvg 211-HARVESYIN6 ON-ROi..e.. 0 2 33 ‘1..° 13 cougyyz_a11:1uflntyc ZY'THE EvO.:.- O O 431“ 1.,.5* 35 ccnggw: 271-HARVESYIN6-ON-ROw..e.. 0 J 28 . , O 13.31 19 COHBYVE 271-'"‘V‘Lva.cx to rat: canv '0 BEGIN "on: Hanvcsf_:wo... o e 13 ‘TUTI3“38“UUH:fV£”2I1-NARVE511ue 0N-n0v...., o 3; 20 18.05 10 COMBIVE 271-!RAVELiYn A IRAN! SE? 70 UNLUIOeOeeeeeeeOeeeeeeOAe 0 ‘ 1’ 'Klus—SET ‘.UEL‘YboO.eOOOQQQ...Q.. 0 ’9 . 'le“ 50 COMBIVE 27l'COKN TRANSFER [‘70 1 YQAVS SET 190.0..0...:::...3..o.. 0 O 32 “ruttv‘*33“tuue:vz‘z1r31RAVEtT1. A rens:c.... o 1 A: 10:50 5‘ TRAYS SET l-lflAVELIYn l FRNSYOeeg. 0 O 0‘ ...-....¢.-.p----ou-Onh-icoaqgo-..p.....--.....I-o-.......=: tnAMsPORT sets 10£~1151£o ABOVEl'EREACOHPOSEO 0! 13:1:.... “'EflYTTT55 -=’I‘i‘3~1 o 6 ...ong....-.O---OGDOVO.......O....ICOOOQDQOQQDCQQOC-O’..... b) Combine Unload Pattern 2. On-Parn Storage Option. Figure 17 (ccnt'd.), 176 ‘ftOCfi*EVffi*—THIS‘EVENY'SIONALS’ENO“OF—VHIT*‘*—’UURITTUN"OF‘ VIME c005 ACTIVITIES roR HHAT ENIITIES THIS ACTIVITY HRS MTN SEC 10.69 29 TDAHS 561 1- SERVICINfi............. o 10 21 10.73 a vanezs 551 l-INITIAL sp0111~o 1~ 7”: FIE!D....o.oo............... 0 2 “ 10.79 8' roams SEI 2- INITIAL swor11~5 IN THE FIELD....Oeoe.00000000000000 0 3 38 “TT7U5“ 13 CfiNRINE 271:§FPVTCIMG............. 6’ 15 3. 11,10 9 CqNRINE P71-IN1TIAL SPOTTING IN THE FltLD T0 BEGIN HARVESVo...o. o 2 26 ~f¥;}T——3+~anMQINE 771-HARVESTING"ON-ROV{7{TE U 5 ‘6— 11,13 la CnNRINE 271-TDAVEL TO A TRANS SFT T0 UNLOAUOeeeoeeeeeoeeeoeoee D 0 ‘5 TquS‘SFY ?: UFLAY...W...JTTTI.....3‘-'O 2.! 36_ 11.19 21 Covylwfi 271- CORN TRANSFER INIo TRANS 561 2..................... 0 0 Q3 "TI;TV’"19_.CfiNRINE Z7l-TDAVEL RACK TORYHEJ“ -_—“—_—_-__w*_ . CflRN To BEGIN VORF HARVESTING... o 0 15 11.35 37 CHNCINE 27l-HAQVESTING ON-ROW..... 0 9 32 ‘11736“”18”“Cn~RIuE‘271-rnAVEL‘TO“A*TR1NS*— SET TO UNLObDo.oegoeeeooeeeoeoeo 0 o ‘5 TDINS SE' l-DFLAYeeaoeeeeeoeeeOoee 0 37 59 ‘11:J6“'2}“’CONRINE 271-CnRN TRANSFER'INTO‘”"‘”"“”““‘“ "-~ . TQANS SFT looeeeo.eoeoooooeoeoee O 1 25 11.39 19 CfiNBINC P71-TRAVEL RACK To THE - "CORN To BEGIN MJHr HARVESTING:.. o 0’ 15‘ 11.67 1‘ COPRIME 27l-HARVESTIAG ON—DOW..... 0 ‘ 46 11.47 13 CnNHXNE 271-Tunwvuo AT THE Ehu.... o o 30 O O O 12.22 38 Cn~RINE 27l-HARVESTING ON-ROW..... o 6 30 Ti:r5—-Tt——CWW=1wE"?71:TRIVFt—TO‘A-TwnNS SET TO UNLOAD-..............-... 0 TUQNS SEI Z-DFLAYee.eeeeeoeeeeeoOO 0 T2,:5‘”SU"‘KHVDTNE_27I:C0QN’TRANSFEW"INTO TCAHS SET 200.000.000.0000000000 0 0 15 12.3; 53 cavaINE 271-rnquL TO A FRMSIU.... o 2 31 T?.52"?S‘_T3hVS"SET‘1:TQKVEC—fUWKN”UFF3" . FARM “ARKET LOCATIONooooeeeeeeee 0 13 l6 12.96 26 TnAhS SEI l-HNLOAUING.COPN AT AN ”” "‘“' "'—*“CFF-FANM'HAQKET'LnCAT10N;:37}:TT“_0"“”25*—"_0"' 13.15 54 TuANS SE! I-TRAVFL TO A FRMSTD.... o 12 57 13. 71 25 101~8 SE! ?- YQAVFL TO AN OFF- M""‘"’”“—’"‘FLR1 uADkET COCATWUNZ........... o 33 ’18—. 14. Jc 2o 1>n~s 561 Z-UNLOAUING CORN AT AN OFF-FA"M MARKET LnCAT10~........ o 35 0 Tn;82”"sa ‘TnfiHS‘SET“2-TDJVCL YOWIFFPVSTDI:?T__i-'§TMH”JI_ l 59 6 6‘ YRAFSPUWT VETS [HENTIFIED AUOVE WERE COMPOSED OF THESE ENTITIES -- 1 : 341 0 “"‘ "' 2 =' 71' 331 “321‘“—*”*’ -;"".---br--;--Ogon---------~u-------n-- ------------------ c) Combine Unload Pattern 3, Ofanarm Marketing Option. Figure 17 (cont'd.) DEMONSTRATED USE OF THE MODEL To demonstrate the use of the model an example 320- acre farm was devised. The physical layout of the farm was as shown in Figure 18, with the individual field characteristics given in Table 8. The particular combi- nations of row length and yield potential were chosen so that all three combine unloading patterns would be required for a 6-row (30-inch) combine with 120-bushel grain tank. Planting of the sample farm was done with a 6-row, 30- inch planter at 5 mph planting speed with 70% field effici- ency. i.e.. about 6.h acres per hour. Planting policy specifications included an April 24 preferred starting date, a May 5 mandatory starting date (even if soil temperature was not up to 50 degrees), and hybrid information as follows: 250 acres of a full-season hybrid, the rest to be planted to a medium-season hybrid based on central Indiana heat unit requirements. The weather data used were composed of actual rainfall records kept by a farmer-cooperator in west-central Indiana in 1976, and daily observations of average temperature, pan evaporation and wet-bulb temperature from the nearest U.S. Weather Bureau substation. 177 prin. field entry points 880. fiEld entry points intended row direction 178 Field 6(160 A) Field 5(80 A) Field #(40 A) v—4rLe—— <&——h- Field 3 Field 2 (20 A) (10 A) t . Field 1 (10 A) ; 5 miles from here to off-farm market #12 Figure 18. T 8 miles from here to off-farm market #11 farmstead /"‘1 LyL I Physical Layout of Example Farm. 179 Table 8. ‘Field Characteristics of the Example Farm. Average Preferred Row Yield Soils Planting Field Lenggh Potential Information Seguence (POdS) (bu/acre) 1 #0 125 100% Type 6 lat 2 no 125 100% Type 6 6th 3 80 125 100% Type 6 2nd u 80 100 80% Type 7 3rd 20% Type 6 5 160 120 no% Type 7 5th 60% Type 6 6 2h0 115 60% Type 7 4th 0 40% Type 6 Four different system variations were simulated with the basic harvesting and marketing policy (and equipment alternatives) shown in Table 9. The mandatory start-harvest date was specified as October 1 (regardless of kernel moisture), with a 22-28% preferred moisture range for high-moisture on- farm storage, and a 28% maximum moisture for corn to be marketed off-farm. Other specifications included: the combine and transport sets were to be stored overnight at the base farmstead: corn could be unloaded on-farm at 1000 bushels per hour plus 10 minutes setup-and-knockdown time ' per load: corn marketed off-farm, at either of the two locations specified. required #5 minutes if the load arrived 180 Table 9. Harvesting and Marketing Alternatives Examined. System Item A B C D —-_—( Combine 6~row,30-inch Same as A Same as A h-row.30-inch 120-bu tank 120-bu tank 350 bu/hr 275 bu/hr Transport 350-bu truck Same as A BOO-bu truck Same as 0 Vehicles BOO-bu wagon ZOO-bu wagon unit(2-150 unit(1-200 bu wagons bu wagon w/tractor) w/tractor) 0n-Farm Hi-Moist. “0,000 bu 5,000 bu Same as B Same as B Storage Provided* * Rest to be marketed off-farm by random selection of a market each day. before 9:00 a.m. or after #:00 p.m., 25 minutes if it arrived between 11:30 a.m. and 1:30 p.m. and 35 minutes otherwise. The one-man labor-force for the systems was scheduled to work 11 hours per day Monday through Friday, 10 hours on Saturday, and 5 hours on Sunday. Off-farm markets were assumed to be Open on Sunday during the harvest season. Planting and Crop Development Results Planting and crop development results were identical in all h simulations. The first planting was done on April 26, two days later than the preferred starting date due to 181 the soil being too 0001 (less than 50 degrees) or untractable on April 24 and 25. Fields 1, 3 and about three-fourths of h were planted on the first day. Additional planting was not done until a week later. on May 3, when field h was finished. and about one-third of field 6 was planted. The next three days, May 4 - 6, were also declared work days, which allowed planting to be completed for the farm at about 3:00 p.m. on May 6. After planting about one-third of field 5, on May 5. seeding was switched from a full-season to a medium-season hybrid. Though planting spanned an 11-day period (April 26 to May 6), all field sections of the farm were declared mature over a 6-day period (September 2 - 7). This small range in maturity dates was due to the use of a medium-season hybrid on the last 70 acres planted. Planting and maturity infore mation is given in Table 10. Potential harvestable yields, set by subroutine YIELDZ, were above average for this particular year. Activity Simulation Results The four system variations (see Table 9) were devised to illustrate the following comparisons: System A vs._§ -- Both utilized the same harvesting and transport equipment. With system A most of the corn was to be stored on-farm as high-moisture corn (short transport distances, 182 Table 10. Planting and Crop Development for Example Systems. Section Section Planting Hybrid Maturity Field Size Numbers Date Type Date Yield gb—f (acres) (bu/A) 1 3.3 _ 1 - 3 8/26 Pull 9/2 138.0 3 3.3 7 - 12 8/26 Full 9/2 138.8 a 3.1. 13 - 22 4/26 Full 9/2 110.8 23 - 25 5/3 Full 9/6 110.7 6 3.2 51 - 69 5/3 Full 9/6 127.3 70 - 92 5/h Full 9/7 127.3 93 - 100 5/5 Full 9/7 127.3 5 3.2 26 - 32 5/5 Full 9/7 132.9 33 - 39 5/5 Medium 9 3 126.2 40 - 50 5/6 Medium 9/3 126.2 2 3.3 u - 6 5/6 Medium 9/3 131.5 relatively fast vehicle unloading). With system B only a small portion of the cr0p (about 5000 bushels) was to be stored on- farm, the rest was to be marketed off-farm (longer transport distances, relatively slow vehicle unloading). System B vs. C -- Both utilized the same harvesting equipment and basic handling options (about 5000 bushels delivered to on-farm, high-moisture storage. the rest moved off-farm). With system 0, however. the capacity of the trans-_ port equipment was reduced (truck size from 350 to 300 bushels, tractor and wagon(S) from 300 to 200 bushels). 183 System C vs. D -- Both utilized the same basic handling options and (smaller) transport equipment. With system D, however, harvesting capacity was reduced from about 350 bushels per hour (6-row combine) to about 275 bu. per hr. (h-row combine). Both combines were assumed to have the same size grain tank. A general summary of the results is presented in Table 11. As was expected, each succeeding system change required more operating days to complete harvest. As the season was extended, stalk lodging increased, as did preharvest and machine (harvest) losses -- total harvest volume (bushels) and average kernel moisture both decreased. Since a variable combine speed policy based on power requirements was in effect, the lower (harvested) yield and kernel moisture allowed a slightly higher on-row operating speed (average) to be used with each succeeding system change. The labor utilization information (Table 11) helps ex- plain the operating-day differences in these particular systems. Handling activities (corn transport, unloading and associated activities) required about 69 hours when most of the corn was stored on-farm (system A). When the same transport subsystem was used to move most of the corn off- farm (system B), the time requirements nearly tripled, to 179 hours. Using slightly smaller transport units (15-35% 1€N+ coma «eon on“: u.nr« clan behNd .epa ~.aow up; o.o .epg a.am~ .eun m.~ma paeaean oonn A.m>a No.~v nus ~o.n : om.~ «an n a .22 6.3 puns neaon .eu: n.6aa eaeaean oman A.m>m méoug nae.65.~ : o«.« “an : a eann aeu one": “OM eon: m. a .mp2 a.anm «we: cad. .mp2 a.maa .epg “.maa eaeaeap mama A.m>e a:.~v ans ~A.N : we.~ «as : 6 “mm : on 0.5 :ON 0"“: m. . .nnn o.nm hovoana Moshe «napaoo can acesndnum oopuaseuood .mun a.mma man o.~ emhn v.00 .eun a.mH« maeaman mama A.m>e ea.~v ans oa.~ : pa.~ as“ u o. emu : o~ nova» Condom neapa>apee .eaaa neapa>apee meaapaem uoava>wpom pmo>umx aoaeeeaaapa begun mommOH GCHSON...‘ comma sou:co maampea xaepm ouspmwofi Hmcuox «enemaeeem eme>uum o a mm a an onw.sn Have» cmvmo>umx a~ 0 p . mu e an o a ma “ua.pxev “MN 0 59 ONQHHfl “NW 0 $9 ON0.0H RMN @ 59 o¢mfad O add-“XEV BMMMIHHO “kw 0 up omo o *uu a an cm: a “mm a an 005.: me a an omfi.un ousvmwoa:cmflm cadpamonudn and :oflposcopm cuou Anzac mcwpaummov asap an asap an asap a« when ma eee>eex me season a sopuhm o sovohm m sopuam <.sovmhm sown ..naeueam casueaov nuance: coavuasaam ava>avo< uo huusaam and ofinue 185 smaller in system 0) added another 97 hours of labor time. While harvest labor increased substantially with the smaller combine of system D, handling activities actually required slightly less time. This was probably due to the transport sets being more fully loaded at the end of each day, and a few more loads being delivered on-farm rather than off-farm.* . Since these were 1-man systems, the time required for hand- ling activities subtracted directly from the time available for harvesting. Had one additional man been available for assignment to the transport sets, then fewer operating days would have been required for each system. In studying the detailed event logs (see examples in Figure 17) it was apparent that the number of (combine) operating days would have been less if the model accounted fln~performing corn transport and transport set unloading on days when combine operation was not possible. In several instances where an activity-simulation day followed a non- activity-simulation day, considerable man-time (and potential harvesting time) was lost due to unloading activities involved with transport sets that had held corn since the previous activity-simulation day. * Recall that the model does not allow switching from on-farm, high-moisture storage to off-farm delivery in the middle of an activity-simulation day. As a result, the model stored about 1000 more bushels of high-moisture corn than was desi- red (or possible) with system D. 186 Accumulated equipment use (Table 11) indicates the appro- ximate hours of use that would have accumulated on engine hour- meters if the combine, truck and tractor had been so equipped. For the combine, in a 1-man system, this is simply the labor time required for harvest activities minus the time required for combine repairs and adjustments, and for combine refuel- ing and servicing activities. For transport sets it is the ‘ accumulated hours in which the unit is nonidle (loaded trans- port or unloaded travel). Activity-simulation days determined by the model are presented in Table 12. September 6 - 12, 16-21, and 30 were declared activity-simulation days with all four systems, as was October 1-8. Harvest (and the overall simulation) was completed on October a with system A. With the remaining three systems, October 5-7, 18-19, 26-27 and January 2-3 were all declared activity-simulation days. The long period of inactivity from the last of October until early.January indicates untractable soil conditions due to frequent rains and poor drying conditions, since kernel moistures were well within the desired range by late October. The soil became frozen on January 2, allowing harvest to be completed. _ With systems 0 and D, two additional dates (October 25 and November 1) were declared activity-simulation days. To do so, however, it was necessary to move the harvesting activities from field 6 to field 5, the next field in the 1537' Table 12. Comparison of Activity-Simulation Deys. System A System I Harvest Unload Handling Calendar Harvest Unload Handling Calender Field Pattern Option Dnte(s) Field Pattern Option Date(s) 1 1 On-farm Sep 06 1 1 On-fsrm Sep 06 3 2 On-farm Sep 06.07 3 2 On-farn Sep 06.07 2 On farm Sep 07.08.09 0 2 On-farm Sep 07 b 2 Off-farm Sep 08.09.10 6 3 On-farm Scp 09.10.11.12. 6 3 Off-farm Sop 10.11.12. 16.17.18.19, 16.17.18, 0. 19.20.21. 0 Oct 01:02.03. 0“.05.06 5 3 On-farn Sop 21.30. Off-farm Oct 06.07 Oct 01,02 2 Oft'f‘rl Oct l8.19.26' 5 2 On-farm Oct 03 27. Jan 02 2 1 Off-fern Oct 08 2 1 Off-farm Jen 03 System 0 System 0 Hirvest Unload Handling Calendar Harvest Unload Handling Calendar Field Pattern Option Date(s) Field Pattern Option DataLa) 1 1 On-farm Sep 06 1 1 On-farm Sep 06 3 2 On-farm Sep 06,07 3 1 On-farm Sep 06.07 h 2 On-farm Sep 07 h 1 On-farm Sep 08 h 2 Off-farm Sep 08.09.10.11 b l Off-farm Sep 09.10 6 3 Off-farm Sep 11.12.16.17, 6 3 Off-farm Sep 11.12.16. 18.19.20.21. 17.18.19. 30, 20.21.30. Oct 01.0%.03.og, Oct 01,02,03. O 23' '07" ' 6 2 Off-farm Oct §§:3?,18, 5 2 Off-farm Oct 25.26.27, 5 2 Off-farm Oct 25.26.27. Nov Ol, Nov 01. Jan 02,03,0b,05. Jan 02.03.0h. 06 05:06:07 3 Off-farm Jan 06.07.08 2 Off-farm Jan 07.08.09. 10 1 Off-farm Jan 08,09 1 Off-farm Jan 11 188 preferred planting (and harvesting) sequence. The harvest activities were then moved back to field 6 after field 5 was completed. Table 12 illustrates another interesting aspect of model behavior. With the bigger 6erow combine (systems A. B and C). combine unload pattern 2 was required in fields 3 and h. With the smaller h-row combine (system D), however, it was possible to use combine unload pattern 1 in these fields. This variat- ion in simulated operation occurred because both combines had the same size grain tank (120 bushels), but the h-row combine collected less corn per unit length of on-row operation than the 6-row combine. This same type of shift in (simulated) operating pro- cedure, from combine unload pattern 3 to combine unload pattern 2, can be noted in field 5 with systems A and B, and in field 6 with system D. . ' In these cases (with a given combine), the shift in pnxndure was due to the particular harvested yield-kernel moisture combinations which permitted the combine to travel a greater on-row distance (before grain tank unloading was required) on one day than was possible on a previous day. The detailed activity state-time information maintained by the model is illustrated in Figure 19 for system A. Addi- tional information, based on these state-time values, is presented in Table 13. Note that combine field efficiency generally increased with increasing field size (row length) for system A. but this is influenced by the stochastic nature 189 TIME PROFILE FOR THE HARVEST SEASON 191. CQQN Cnoe: CORN HARVESTING -- COMBINE 271 .-.----.-‘---------O----.-----..--------------,-.'-.-"-..- ~FYELD ’ HOuR§ IN ACYTVITY STKTES FWELD N0. 1 2 3 4 5 e 1 a ToTAL: QQOCC-h-C------—------O-CCDCem--.-00-------C---'Q-----DQ.--.. .0 .2 .3 2.5 ,o 1... .5 1.9 5.? e0 .23 .3 2e? .3 .1 .3 3.3: 76e7 01 .0' eS 50? e7 .9 08 3e8_12521 .z* .7‘- 1.0 878 1.1 .7 3.2 6.7 20.0 .5 .1 1.8 18.1 1.9 1,9 7.5 17.1' 04.5 .9 .9~ 2.6 36.3 3.8 5,: 5.5 36.9 92.7 STATE ‘ TOTAL 1.8 3.0 6.0 73.2 7.8 10.3 10.6 69.6-192.s_ ..me-Iepuoufi-DD-oeegcm-Q-II-POUCII-cod-oovfll-un-p-OD-DC..OO.ODO-OOO. omauww CORN TRANSPORT -- TRUCK 3A1 -----------oooee-co----.-"'--u-~-p-.--.-.OQ---P9.-P--OQCb-Qo. FIELD nouns 1N ACTTVITV 51.125 FTELO- NO. 1 2 ‘ 3 e 5' a: 1 e TorAgi guns--c-C-----.-----P-"'--'.-.-usOC-.-cn¢qup-C-oo-'.¢-ovu. 1 e0 .0 1.8 e‘. .0 ,0 e0 05‘ 6e? 2 lel .0 3.2 e3 .0 .0 e0 3.1 6e?' 3 O? .0 3.5 08 .0 .0 .0 7.6 1202 0' e6 .0 5.7 leZ' .3 ,0 .0 12.0 19b? 5 1.3 .0 6.8 1.3 .5 .o .0 3¢.7‘ 46.6. 6 2.6 .o 13.6 2.9 ,:.o .o .o 72.1- 02.:- .-'----"--------------".--O-n.p-O.----..Q---OO--QQcow-o... STATE ‘TBTIL ‘578 .0 33.6 6.8 1.9 .o .0 13¢.6~182.T‘ 99......O'COCC-C---.-.-..-.----.-.-UCOOOQCOQC-PQ.-..I"'b..'. CORNFYRAMSPURT .--TRACIUR 7I*. MASON 33f .-waeo~ 321 .q.-..-----.----OO-C-O------C-..COCO----COO-OP..-..-..9--.-. FIELD HouR§gIN nchvrTv slths IIELG» N0, 1 a 3 4 5' g 7 e TOTACi pa'oO-D-OOCQC-npgnago-0--.------.--o------.--DQQ---..Q--.-.. 1 .0 so 00 '0 e0‘ .46 .0 50 eg_ 2 ‘0 e0 e0 '0 e0 .0 so .0 e0 3 '0 e0 e0 '0 e0 .0 e0 .0 e0 ‘ R 0 I o O o . 0 O o n 0 O o m 0 JJ 5 4202 so 6so. 1'1 ' e5. .0 e0 30.‘ 00e23 6 4.2 ,0 13.2 2.6 1.2 ,o .0 11,0. 02.7' DO--.-.'---.------.-~---------..p-.---_----Q--sl..pu-ucflchcg. _SYATE TOTAL 6.4 ,0 19.2 3.3 1.1 ,0 .0 101.8 132.9 ’9’-.----0-0----a-Dav-0.---Dogu...On--.-.-..--..-no.and-a... Figure 19. Activity State-Time Information for System A Equipment. i;— 190 . .Ame>«uu ooswammo cm psonpws msavwmsv m opdvm mchsaocw Po: .caoam some ov commode oEHP Hmvov 029 so commmufifi .Amvcomms can novomup on» mzan gauge on» u N .zaco gosh» 0:9 u a w .hosoao«MMo madam opsaaoo op poms mew» Hmpop one no woman re .caoaw some ca mama» copwo>hwg owmno>o so oommm .+ .As+o+n+s+m+~ epepe\o opdpev.ooa me popsdsoo a. .vocoo: :03: use some mo peeve on» as unopmsmoh 059 pm cosmomaom mm: sown: Am opmpmv mafiaoshon use nonsmopcdma magma ovsaosfl meow van .Am opmpmv msfipflms caoam:cw no: AH opwpmv Ho>mav uHoAH:Ho:pso ovsaoca pom meow ..o.H .Am+m+m+¢+m+m ovmvm\$ 09mpmv.ooa mm copsmsoo .x mmm. . ”Hm Hmm. mm. o . mm owsuosé wen u suemuco awn . mum .ma 0.50 o mmn N sudmuco awn omm oa m.sw m owe a . andeuso «mm mom m o.so s «as H suem-so sam .mom ea a.mo n mom a ssduaumo sum Hmm m a.mo m was a essence sum .mom an o.sm H Aas\snv Ansxsnv Ang\spv Amy was zpaomamo Annomm psfiom madam:cH 309::0 seesaa a.mmm vaowm wfiwswasmm .oz hmo>waon + pace mo ocfipsoo “annex madam +muopomm Pmoamcmua . muopomm vme>mmm .4 Seesaw pom moapmapdpm msaflsem use weapme>sem .ma eases 191 of repair and adjustment activities, and the combine unload pattern required. The lowest effective combine capacity (278 bu/hr in field 1) is 20% below the farm average (300 bu/hr). The highest capacity (about 355 bu/hr in fields 2, 5 and 6) is 3% above the farm average. Using the state-time information of Figure 19, it can be shown that if a multi-man labor force had been used with - system A. with an adequately sized transport subsystem. i.e.. no combine delays waiting for transport sets to return to the field, then effective combine capacity could be increased by nearly 18% with on-the-go unloading. This would be due to elimination of the corn transfer activities in fields 1 and 2 (resulting in a 10-12% capacity increase for these fields), plus elimination of the extra travel required for grain tank unloading in fields 3 through 6 (net 17-21% in- crease in these fields). The effective capacity of the transport subsystem with system A (Table 13) decreased in almost direct proportion to the transport distances for each field. The range was from 692 bu/hr in fields 1 and 3 (corn delivery on-farm) down to 368 bu/hr in field 2 (corn moved off-farm). SUMMARY AND CONCLUSIONS A computer simulation model was developed for evalu- ating the physical performance of the corn production, harvesting and marketing system of an individual firm. The model was structured to provide the capability of evaluating numerous user-specific variations in land base. equipment inventory, labor force. and management policy. The model developed utilizes two basic modes of operation: 1) a daily simulation technique for environmental and management factors associated with the system -- soil and crop attributes (weather based). and operating procedures or labor availa- bility (management based) may change from day to day: and 2) an event-oriented simulation technique for the performance of functional activities associated with the system -- tillage, planting, harvesting. crop or supply transport, and other activities. The development of this latter aspect of the model was completed only for a one-man system, and only for the field shelling (combine harvest) operation and the hauling activities associated with it for high-moisture storage (on- farm) and off-farm marketing direct from the field. The model consists of a very small main program and 130 subroutines that are 192 193 called as needed.* Of these, about 45 could be classified as input-output routines or those involved with the daily simulation aspect of the model. The remaining subroutines were required for the detailed activity-simulation, which utilized the filing system and event control features of the GASP II simulation language. In developing the subroutines. each was tested indivi- dually, or with a few related subroutines, using a special program designed to test the mechanics and logic of the particular routine. Even with this approach, numerous errors were discovered in the first attempts to run the model as a whole. In the author's judgement, however, test- ing of individual subroutines is essential with a program of this magnitude. Certain unique features of the model appear to be adequate. and necessary, for realistic_performance results with complex multi-man, multi-machine corn production. harvesting and marketing systems -- even though the current development was not sufficiently complete to adequately test them. These include: 1) the definition of activity periods based on weather. soil, cr0p and/or management factors which permits the specification, and determination, of field oper- ations and other activities that are feasible at any point * This program was so large (about 18.000 punched cards, in- cluding COMMENT cards) that it could not be run on the CDC- 6500 systemsat Michigan State University or Purdue University without utilizing an OVERLAY programming technique. Even then it required a maximum field length of 36,500 (octal) to load, and 115,100 (octal) to run. ' 190 in simulated time: and 2) the definition of a field-opera- tions-status array, or similar accounting device, to facili- tate scheduling and to maintain the current work/no-work status of fields that are to receive various field operations. The input specifications to describe the physical as- pects of the farm, the equipment, the labor and the manage- ment policies to be used appear to be: adequate for using the model as a research tool. From a practical standpoint, however, farm managers are not yet ready, or willing, to spend the time needed to supply the information requested on the input form -- it simply requires too much detail. In demonstrating the use of the model with the example farm and systems devised. the daily simulation portion of the model performed in a reasonable and realistic manner for the single crop-year simulations. It sequenced through the required activity periods (planting and harvesting). main- taining and adjusting soil and crop parameters, and updating labor and management factors to allow a realistic declaration of activity-simulation days, and reasonable results for ' harvest conditions (yield, kernel moisture, stalk lodging, etc.). . Similarly, the event-oriented portion of the model per- formed in a reasonable manner, given the limitations and shortcomings previously discussed. The accumulated times recorded for the combine and transport equipment in the various activity states were quite comparable to those one might expect in the real world. The stochastic technique 195 used to schedule repair (or adjustment) activities adds a spontaneity to the simulation that is quite realistic -- the farm manager cannot predict with certainty when a repair or adjustment activity will be needed (until it is needed) or how much time will be required to perform it (until it is performed). On-row operating speeds and field losses determined for the combines were well within the range of on-farm values with present-day equipment. Another unique feature of the model, the provisions made for declaring an activity-simulation day on days when field work cannot be done, is also an important concept for realistic simulation results -- though use of this feature was not made with the present model. In the real world non- field activities do occur on days when field work cannot be done (equipment refueling and maintenance. corn handling. off-farm marketing, etc.) which permits a more efficient utilization of available field time on those days when it can be done. Use of the event-oriented, discrete-object simulation technique (with GASP) provides an effective means of analy- zing the state-time characteristics of equipment systems operating under specific management rules. As it developed in this study. however. it was quite a complicated program- ming technique. It's use can probably not be justified for analyzing a simple one-man, one-combine system with no on- farm drying or storage. Its capabilities should prove 196 extremely useful, though. if the model is expanded to facilitate the analysis of more complex systems. The example systems devised to demonstrate the use of the model each required about 60 seconds of execution time with the CDC-6500 system in—place at Purdue University in September. 197a -- 51 seconds for system A, 55 seconds for system B. 68 seconds for system C and 65 seconds for system D. If the capabilities of the model are expanded in the future, then execution time requirements will also increase. which may be a deterrent to the model's use. Certain features of the model developed are unique in comparison to other simulation models that have been deve- loped for crop production systems. For example, the capa- bility of simulating a series of several field operations (and their necessary support functions) rather than just the soecalled key operations (planting and/or harvesting). The capability of realistically evaluating the interaction of field equipment and/or transport subsystems and/or grain receiving facilities under specific operating policies and with specific physical constraints (field shapes, field arrangements. road networks, etc.) is another example. These capabilities. however, were not without certain ”costs”: complexity in specifying input information, com- plexity in programming, especially for the activity-simula- tion. and relatively high computer storage and execution time requirements. Because of these factors. the potential 197 use of the model is probably not, as was initially hoped, as a management tool for practicing farm managers. Rather. its most important future role may in develop- ing realistic performance coefficients for other simulation or optimization models -- particularly field efficiency values for equipment operating in specific situations. Another important use may be for sensitivity analysis, to determine what policies, procedures, characteristics or other factors significantly affect the performance of complex crop production systems. Such information could be used to establish criteria for developing simpler models for research and/or practical management purposes. RECOMMENDATIONS FOR FUTURE RESEARCH The simulation model, in its present stage of deve- lopment. is not a very useful research or management tool because of the major limitations imposed on the types of corn production, harvesting and marketing systems with which it can deal. In order to approach some significant degree of usefulness the activity-simulation portion of the model must be expanded in the harvesting and handling area (event routines developed) to accommodate the following: 1. A multi-man labor force (single combine) situation. 2. Equipment maintenance and other activities on days not suitable for field work. 3. On-farm drying and storage with batch and continu- ous flow driers. and/or with in-bin layer driers. 4. Off-farm marketing of farm-stored corn. The first and third of these will require major programming efforts: the second and fourth very little.* Activity-simu- lation for production field operations should also be deve- 10ped if the potential of the model is to be fully realized. The model-framework to allow this expansion is presently in- place. * As was noted previously, an additional 27 or 28 events were identified (and flow charts developed for the event routines) for the multi-man, single-combine system (with no on-fanm drying). The development of these subroutines should consti- tute a "major programming effort”. 198 199 Two of the programming techniques utilized should be seriously re-evaluated if the model is to be developed further. These are: 1) the partitioning of the farm into 100 field sections of approximately equal size. and 2) the generation of repair intervals and repair times as needed during execution. In the first case it is felt that the arbitrary partitioning is unnecessary. and results in duplicate computations for too many field sections that have a common soil type, a common planting date, and a common corn hybrid type. With the (GASP) field file, and the Di attributes being used, section boundaries are only important to the activity-simulation in regards to on-row length. tractability and the potential harvestable yield-kernel moisture combination. The following alternative scheme is proposed: Basic field sections should be defined for the farm on the basis of field boundary deviations (row length) and soil type. Subsections would then be defined during the planting operation (a maximum of 100) based on planting date and hybrid type. In sequential-year simulations the sub- sections would be redefined each year during planting. In the second case, the present method of generating repair intervals and times makes it difficult to compare two or more runs in which performance or management coefficients are varied. A better technique would be to generate an array of random numbers for each equipment item that is subject to repair (or adjustment) activities that could be used on a 200 whole series of runs. This would eliminate the situation. for instance. of the nth repair of a combine occurring after p-hours of use on one run, and the nth repair of the same identical combine occurring after q-hours of use on the next run. In developing the daily simulation loop of the model. provisions were made for inserting a block of programming instructions to collect and/or analyze cash flow data on the last day of each month. The development of this portion of the model, plus the inclusion of other economic aspects (fixed and variable costs, corn prices, etc.). would greatly enhance the ultimate usefulness of the model. In addition to these programming needs, much research is needed to document performance and activity-time coeffi- cients of field and farmstead equipment, both operating and non-operating (repairs and adjustments), for simulation programs of this type. Management policies regarding the assignment of men and machines to perform alternative activities also need to be studied, interpreted and modeled.' APPENDICES APPENDIX A 72()1 APPENDIX A COMPUTER MODEL INPUT FORM The input form is divided into three basic parts to obtain three general types of information. Its organization is as follows: {arm buyout Spsgificatigng Section 1 -- Geographic Farm Description Section 2 -- Field Size. Yield Potential and Sells Production Spccificatiogg Section 3 -- Field Operations and Operating Policy Section A -- Listing Available Field Equipment Section 5 -- Allocating Equipment for Field Operations Section 6 -- Production Labor Force Harvestigg and Marketing Specifications Section 7 -- Harvesting Policy and Equipment Section 8 -- Corn Handling and Marketing Methods 8-1 Wet (High Moisture) Storage Option. 8-2 In~Bin Layer Drying Option 8-3 Batch or Continuous Flow Drying Option 8-0 Direct-from-the-Field Market Option Section 9 -- Corn Transport Equipment and Policy Section 10 - Harvest Labor Force SECTION 1 -- gggonlrurc FARM oggcarrrrg! A farm map similar to the one at the left is required for developing computer input. Features of your map should include: l) Drawn approximately to scale. and the scale noted on the map. 2) All fields are shown and identified with letters or numbers. 3) All roads and farm lanes are shown where they are. h) Physical obstructions within fields which tend to reduce the efficiency of farm equipment are shown in their approximate position. e.g. the woods in fieldsll and‘g the pond in field H 1' - 80 rode the buildings in fields g and g; the grassed waterways in fields g and Q etc. Note —- Obstructions that are not email identifi- able on the maps submitted shou d be labeled as they are here. TWO COPIES of your farm map must be submitted with the following information noted: Farm Map #1 Coding of fields and planting policies. Farm Hop #2 Coding of transport and travel dist~ ence: and routes. The technique for doing this is explained on the following pages. Sample Farm Map l -. l' - 80 rods 18-30" headland rows when planted 9! Sample Farm Map #2 _- 800M i i ‘L p US 27 l" I 80 rods orsrmcos "or 'm scars _ n-B 0.6 mi. 27:." yollo B-C 2.2 NIL: blue 202 Cris'inaflfida L11! “1awnibzxgntjjfliflgz -- atrium; 1) Plunt in'_iefitqng, Indicate the ~lnntin; puftnrn used in each lield. 'hH)|‘HIfiL rnn are pns:;l In: ‘Continnrue, _13;L__ 'ontinnous, ultnrnei' n' pattnrn nu inv‘itntuJ in n plvtt-rn ar indicit-:T_ln the ficfd 5. Tu" pnt‘71n in , at 01' tte fields. Tue limits! to clockeiuo ' arrow snould show the ‘plhntlm; unzi uux‘W‘:1.lr2';. ,‘_ parinftlpul row direction. ‘0 3 h Hondland howse-whorn. indicate for each field where headland Tend) ruwh or fxrn roan nro pluntcd with t\' aymbolAM-~rias lllU'LPitGd).'f1Pn roue e.\tubl i~t~d for harvesting in "lcn;" fiel.da mn; b-e inliontcd at the halfi.a} roint, or at the 1/3n /3 point in the field, as i-lu:ttruted in field A. dhc heuilnnd rows are not indicated in a place where a turning urea of some type will be needed, for inatence along the north edge of the greased waterway in field 3, then a turning strip will be assumed to exist outside the ‘illahlc boundary of the field. V ) Headland Eons-~How Manx. Indicate on the map the number of headland rows planted: when planted-~fixed for the whole farm. ) Planter Suppl; Vehicle Location. For alternating patterns, put an‘X glen; the end of’the‘ffild whore nlnntor refills are made. For circular PJtCOPHS, out an X in the general location of the field entry noint used for the planter supply vehicle. 5) Field Number Ccdin . Computer-code "fields" by numbering con- 1) ncCuEIVOlyffrom --up to a maximum of 30, then circle the new number for each field. A field currently identified by a single symbol, number or lett'2r, should be divided into 2 or more "computer fields" if EL; fi*11 is not planted in a con- tinuoui mannnn. F0“ instance, ?'9 eld‘gg at th u left W‘s- been codod as_"?ields" ann , 1.9. tie grassed waterway must have been too deep or tu>rough to cross with equipment so the field is planted in two parts. Note -- This completes the information needed on Farm Map #1. Coding Transport and Travel Distances and Routes -- Farm K90 #2 Field Numbers. Cross out or remove the old field identification 5;.mbcls from this copy of your fern map, and enter the new coded "field" numbers assi :ned on the otrer copy. Use these new field numbers throughout the rest of the input form. fond Type . Use a 3-color code to indicate road typos. Note on t. 0 map a legend of what the colors stand for. The road types .f interest for tie computer are: fern lqggg--the road actually is, or is equivalent to, a be..:a11y solid, narrow, ell-weather road, but with a few soft spots(\fter rains), rou<1 spcts. or s‘arp turns wh. ch limit both farm equipment are .rucks to about 8 to 12 mph avern*3, or less. _1 vol roads--~:ho road actually 1:, cr is equivalent to, a sol; n, 1‘11-vectler road with CAI; occasional "wash-boards" nuch that the road itself does not limit farm equipment Spends, and trucks typically average 2“ moo,on short runs o“ wh<.n {'11, up to 30 mph, on long runs r u en empty. hard 3‘"T5 .~:d rcuds--the roxd actisl.J is, or is equivalent to, a g.cd ccuni;r;, Placktop, .it: "err little "wash ':oardin§ , or a state o.~ federal highway ‘won that trucks may average 30 mph, on snort runs or when full, up to LO mph, on long runs or when empty. {it-n: C'filtv Foin.s. Mark with a 11.32;: dot,_-l._, the location of entry points into each field from a farm lane or public road. Hark with a white dot,-€}, the locations where one field may be ~nt~rcd from 91(tne.. Do not mark entry points, even though the" ‘o exist, if they are never used or shouldn't be used. inc) field must have at less 5 [ oxzr y poi'—E”01 one thc or other. Ll_g}ln' Diutanogs. If fields or farms are not connected by z :1 on \our f';n map, like fiilus 6, 7 and fields 3. 9 at t e left, then idunt ll reference poin.s, like A, d. C. and D at the loft, and indi:ute the travel distances and types of roads between these reference points. (continued) 203 '3“m910 POP“ ”0P #2 (cbnt.yr Coding Transport and Travel Hiaggnces and_£yutqi (continued) 5) heai~nation of "Fnrmateada". You may daeirnute up to 6 differ- Zfit‘"rirmsfana§" T6“F3"uaad later in communicating various policies to the computer. Thane nolicies will relate to: -the out-of—finld location where tractors. combines, trucks, etc. may be refueled, maintained, or stored overnight. -the location where field enuicment or supply vehicles must go to get additional supplies of seed, fertilizer. etc. -the location where harventod ccrn is to be taken for on-farm drying. handling, or storage. For some policies you may want to indicate a specific location, while for others you may indicate simply the nearest “farmstead" to whero activities are taking ulac~(see note at bottom-left). ”Farmstesdn" that you feel will he needed shculd be coded in the table below, 33$ noted on your farm map. They need not be phys- ically located adjacent to one of your fields. If a "farmstead" location cannot be shown to scale on the farm map, then indicate in the table the distanggianl road_tyneg)_to reference points on th° map: [?ulJoo's storage hinn:f‘; 21' E35 r??ié;}’t° point 3] You may wish to come bacE’here and identfiy'fiare or different ”farmsteads" when the policy decisions are actually being made in later sections of the input form. l" - 80 rods C . 5 nos n e d were designated "farmstead" here to use the policy of storing field equipment at the nearest "farmstead" at night, i.e. it will be let in the field when working at the two outlying farms re erence po on your arn map. or arms that cannot be located to scale on your map. Sample Farmanap #2 (cont.) Coding Transport and Travel Distances and Routes (continued) OOH {L7 yes 6 Designation of Off-Farm Locations. As with "farmsteads”, you E *W‘CS may designate up to 6 off-farm locations. These will be used main in much the same way as the "farmsteads", except that the policy decisions of interest are only those dealing with the transport of production supplies and corn: - the off-farm locations(if applicable) where field equip- ment or supply vehicles must go to net additional supplies when needed for a particular field operation. (Note-oThe computer program is not concerned with supplies that you obtain off-farm in the "off-season", Just with those that ‘F ” L you might get off-farm while the field operation is being , done. (:> (:) ' -the off-farm locations(if applicable) where corn may be transported: directly from the field, after drying, or v Us 2? coded in the table below. If their location can be shown to after storage on the farm. ht“"“ Off-farm locations that you feel will be needed should be scale on your farm map. then do so. Otherwise. indicate in the table the diatance(and roadgtypes) to r?€orence points n on your map: ..3 mi. -—— yel. 1 I 80 rods Ed3 Daly elevator 0.7 mi. ——f (blue) to pt. 8 You may want to come back here aid identify acre 0 - arm locations when the policy decisicns are actually being made in later sections of the input fern. Cl‘ 1‘ a Fl 6 o re erence po on your arm map. 204 EEOIIQN -~ [IELD SIZE. YIELD POTENTIAL. AND SQIL§ Three additional types of information must be supplied in the table on the following page: i) Tillable Acres. The dimensions for each field will be taken from your scaled farm map.and used an input to the computer. The computer will automatically make minor adjustments on these dimensions to obtain the specified tillable acres. 2) xield Potential. During computer runs the net corn yield for each field will be determined by: -- planting date and hybrid planted -- growing season temperatures and moisture stress. and -- the harvest date and harvest losses. In order to make this accounting. a magimum yield pgtgntial is needed for each field. Because of the factors just listed. you've probably never seen the maximum »otcntial from any of your fields -- it may be 5 to 20% higher than the highest yield you've ever harvested. What is needed is a realistic. “no- holds-barred“ estimate of maximum yield potential ‘ -- assuming ”ideal” or optimum" planting time -- assuming a good yielding full-season hybrid is planted -- assuming “ideal“ or "optimum" growing conditions -- assuming your current fertility level or program (this will be held constant for all computer runs) ‘ -- and assuming zero harvesting losses. Give your best estimate for each field with these assumptions in mind. 3) Major Soil $ype(s). The water holding capacity of the soils in each field is important from the computer standpoint in determining moisture stress during critical periods of corn development. and in determining how soon field equipment can operate after rainy spells. This may be indicated by giving one or two soil type codes for each field. Soil type codes to be used are: SAND loamy sand sandy 16am DOA” silt loan Slim silty clay silty clay loam clay loan 10 CLAY 11 sandy clay 12 sandy clay loam Code i ‘OOQGMNN Percent SAND .13 . 03x. 0" C) of Yield be p 0. so .n o Tillable Potential Type,?his Typc'Thi ; C a I a f‘ ‘3 4 un r . .ax. of Yield so .: o o . Tillable Potential Iyps:fnis type; c ' e ICcdc T . 205 {MOTION I -- FIELD OPERATION} and OPI'ZRATI'Y} POLICY So that realistic policy decisions can he handledinnd communicated to the computer). the crop-year is divided into 6 netivit periods -- S for producinq the crop. and i for harvesting and marketing it. The nu;.nninfi"unw*endinn of these activity periods have been defined so that they depend on weather and crop development fuctors(aeo table). as such. some of them may overlap, and their actual calendar dates will change from year to year in the computer. This is illustrated below. ILUFI nbvl UQEI Lest Year's Next Year's TE '] f" [V 7] Crop Crop I This Year's Crop [-1/6!]T’Yi'3]71fi'£].tl.l.11‘.'.‘{[JUN JUT. MD 7.7.? PC? NOV DEC ‘1 r“ .2 f 3--———'> l l -J—-h—Ja- 1 : 51—» a ,----.-.--, l:Fall Land 3:?re-Plant(5pring) Preparation Land Preparation 6:Earvest and Marketing Zzwinter Land h:P1anting Period . Preparation 5:Post-Plant Tending Period fictivity ?eriodr “ccinninn/Rndinz. Various Activities Possible Chains lat harvest date all tillage 915 land preparation jobs #1 of last year's crop. including fert. application of all Ends ween soil freshen, types-~3nreej, riowdcwn, xnifedown.__ , :eqins with soil frccye. stalk chopping or shredding plus J2 Finds with spring thaw. serendin'; Wart,J but no tillage. engine with the spring nll‘land prep. jobs not "tiid to"vthc Production #3 thaw. Ends when all the plantin1-—those that could be done a Periods corn isAplnnfied. few hours or a few weeks before plntr aging with potential Planting plus those jobs to be done #h date you specify. Ends "right before" and "right afterwards: when all corn planted. i.e. separate but ”tied to" planting”.4 begins when any corn Operations to ccntrol weeds and other #5 reaches h" height. pests--rotsry hoe, cultivate. and Ends when all corn spray--plus knifedown nitrogen reaches leyhy height. nonlicetion. Harvesting angina when you specify. harvesting and hauling. plus any and #6 Ends when all corn is on-farm drying, handling. and Marketing harvested. storage operations. Define Field Operations. On the following page you may define a maximum of 5 different field Operations for"each production activity period. All Operations listed should be done. dither totally or in part. by your equipment or your labor force -- do not list operations that are done entirely by a custom operator. You must list planting as one of the operations in period #u. Boyo§7.this requirement. you may list operations for all or none of the other periods. Enter a name or brief description of each operation you want the computer to perform in each activity period -- either on the total or part of your corn acreage. ch will have a chance later to restrict certain operations as to acreage or fields in the various periods. So if an operation could potentially be doncior you would allow it to be done by the computer) in one of the activity por-oda. then list it for that period. A number of Operations might be listed in more than one period. For instance, bulk spreading P and K and chopping stalks could be listed in periods #1, #2. and #3; plowing could be listed in periods #1 and #3; or knifing-in anhydrous could be listed in periods #1. #3. and #5. In listing operations, keep in mind that with this computer program you may apply a maximum of one material-~fortilizcr. herbicide. etc.--with each Operation, except for planting where the maximum is h materials. including seed corn. If you plan to cultivate your corn twice. then list let and 2nd cultivation as separate operations. Assign Field Oeeration Code Numbers. Next. assign a code number to each field Operation--nun- ber consecutively flan El up to the maximum number of different operations listed. The same Operation listed in more than one activity period should carry the same code number in all periods. ' Ordering Field Operations. Next. assume for the moment that one of your fields is to receive all of the ep!rationa’listed. For each operation listed, enter the code number of other oper- ations that it should followiDo Aftr Qper), and which it should precedeiént Bfor Qperi.M_Use the following where appropriate: Lper 0 ho anytime aftcr‘lhst your’s crop harvested. 0.6. discing stalks or spreading Cper 99 no anytime before corn reerhee layby_hei;ht. P and X may be done anytime after the Field'is harvested; cultivating or sidedressing I must be done before the corn gets too tall. H N indicate Field Pattern 930d. Next. enter a field pattern code number for all operations except planting, which was previously specified for individual fields on ycur farm map. The field pattern specified for these other operations will be used on all fields where applicableises box). Maintengnge_nnd Overnight Stnrgfie of F uigment. Next. indicate a location code for each Operation 1375 box) whichnlescribJFH§5fiF pr cy 6r rJTUeling and performing routine daily maintenance on field equipment. Then enter a location code for the overnight storn:e of field equipment. if you assume the equipment will be used the next day. Your policy regerding these two items may change over the season for an operation that can be done in more than one activity period. (continued behind the table) 206 5 p ‘ V'”C_“ -49” -7Q_ ” :4” - ';_-1 k 2:.;' .in!d_juttcrn Codusz Upcro:QCn .n Pu “L Li ‘le- var .11". .. x ihoao Flues *%i?3}«71 " mm or » ”'- -.’c- Soc 5: int :ism a.m. . ‘:: um. “h. :r. Col;1 Doecri tihn Q5; rm .n ,un” ode (min . t l)? {/1 " " i ' “- F ii - 7 - ' {End " . q q (:0sz Prep ‘ U Alternating rntternfi‘ .777“) —' '1 God I}: LBJ 2‘, ALL 135.2773». terns. —‘A-“ afot available for circular-planted , pnpgna 3h ficlls, where u Jsc {Sole 0;” circular pattern It :310 for .'".)'it 5". “sad for the 090,851 3:1 operations. rcntricted to crtain hours aoh fay. ‘Cfation folcs: Q: n the 11616 where used. l-Stst the farmstead (£1 to £6) which you oncoify. 7=at the farmstead nearest the fld. where gggd. (main field operation table continued) Idle Time for “sols. The computer will schedule a meal-atop at 12 noon and 6 PM for all field equio~nnt overntin; at those times each day. Any value you enter which is 5 minutes or larger will be churged to th: equiomont nrd driver(s), You may indicate that a relief driver(e) takea over n ccrtain operation during meals by entering a value cf h minutes or less for it. It you do this, and then a relief !r1ver is not available, an idle time of 30 minutes will be used. This policy also may change over tho season for an operation done in two or more activity periods. Potential Cnily Qpnrfiiin? Hours. Each operation will he performed by the computer each day only ~‘T‘_ . ‘ t . _‘-"r‘ id'— 5 ~ I -s as ion, as there is inocr 'VdilflJIO to co it. (labor hours are specified in section ) However. for some operations 12! nnv High to rdctrict than to certain hours each day. For instance, n fertilizrr nnolisation jaw may be limited to the hours when the dealer is open, or you might want to limit alontin‘ or anathor oocrotion to da'liPht hours onl . In those cases thcre no be other i 5 f a _ 7 y jobs which available laws: cculi dc to finish-cut the ony. for each operation. in each activity period, either 1) chock tun Labor Hours AVLilnhle box. 25 2) r‘ntcr the particular hours when the Operation can be don». g; you restrict plunting, Rni a‘sociatod ooorutions, to certain hour. each day, than you 11;:; w;nt to alter int: SJHQ to refle:t the importance of timeliness. e.g. you might ha willing :0 run the equipnnnt longer hours each day if pinnting is still going-on, in the computer. in early June. This can be shown here, IF it applies: \' not}? C i ""3 I'inzi .. i—l'i'g ‘HW.{TE , I" ”V ”' §w3 Q h! n 'y ,u Note -- If you enter starting and quitting Lon A» or .. (.sc A” or I“ ~ , fr 1‘ times .cr an cycrction, but fail “ J to in3icate enough labor in the labor section to run this many hourc, then the ororntion wil be limited each day by lJbor hours. Note -- The planting period is broken- doun into the three time periode shown at the left in the labor on-y or .oec opera. on: app es , any. section also. Cther policy docisinnn for the field oonrutione won have dcfinod pro continued on the next rune. Go thare only oTtnr completin: thv tnhle on the rrcvious nogo‘nnd the one above. if applicable). 207 fl~wtrlctlcna lunnd "n g -h____«_M_“"-u,-___-uhfifllffl,"QZEFQQ- (Skip 1f full nnd . tn ‘ .nnuo n a any race allatar «4vur:nLlex' yu‘L .wlurrxuatfl El»u nuny In; tr~1ct ltlltxi‘n p'? t‘u:.o;w-ratl(-n llJPlr" the 5’ 1 Owhrntl(fin plunqnn for thn fall nnJ Hint-r uctlvity nnrlods v“v nu? J'Htor a~tl" t,” 1 .n due to tho eronlun nr run-off Dnljfitlnl on purL I 1“ of your u~xvnpe. lor 1n1Lnnnn. you nlqht limit th\ applicutlnn of f rtllizer, or Full n‘rulnfi to only a few fields. Enter tnu field opnrutlnn coda numwr‘a) and the code :11nber(3) of the floldn whcro tho operation £33 be dona. Egggrictlcns nfiliqflgfl_gflflflifilfint Plignlng. (Skip if not uppllcaule.l You mug plan :0 prrtorm cartuin operations on only part of your total acreore oath Vunr, fink You rotate this acroaze so that eventually the total acreage is cov’red hxumalcsz Hulk anrenilng P and K on orly half or a third of tnc total ercu;e eu'h your, noldurard plcwlng or chiaal plowing only a nortlon of tho total each year, etc. Entnr tho field covrqtlon code numberfsl un* tho phr cent covered each year, or :5? numbar of your: required to got over the whole ocrnogo. 1d. Oper. Yrs Re Field Numbers Groupe As You a 0 we not Freq. To Cove ode (yrs) Whole A. em First year fields grouped together. 2nd year fields groupd together. etc. ”'atrlctlona PlannedJ 7ut Sonlgfiqgflfillfgj. (Skip If not 3 Tllcnglofl—TFWHEHJ Exam to rerfrrm c~rtnin onnratlcns on only part of You? tct1l ncrvnre eqnn lenr, but ¢no part ‘ . Th5 cvverri wlll coprnl cn weathnr, s>!l, and crop conJltionn. Elanalea: Honnrf hoeing, ”lrs: or se:cna 21l21Vution, 9;ct- triatnent wiLn 1 Into annoying, ct(. Later trh “told 0:9rs ation :udc numbnr(1) unl tna par Cunt of total acrwaqa to be culnred per vnnr. fnis acrcqgo rill be choson randomly on a {;vld basis oacn your, or you ray lndlcato(Cpticnnll certain "problem" fields cunt should receive tno operation ovary vear. s . s e To Resolve na- C‘Efllflnilt131_:lfllfl.§ZCV3£3°”" {Skip if not applicablo.l Cortnin flald oper- Pairs of Fld. 0p. :fluns nu} ma nrrnlvm-uturi~lfi tne sansc that if a field rncelvua cno, then Code Nun it should not rccolvo another cnn. Zxanp1c1: You may want to mkldbcnrd plow par: of vcnr ncrnuuo, and chisel plow annth¢r nurt, but no field should ro- colva 10th. Also, tnn various nnfihodn of nnplylw; hulk nitroqnn should ho inltra'od u: cowrllnsrtnry -— surface arraaf or Jrrnylnv, plow-down with a nvldbnnrd ur nhlswl olca, nnd knife-down nonllcutlcnlnrurlant or sidedress). Enter the appropriate field operation coda numbers, if any. 208 EEK21l71”22-P1911“9D"‘"""“" Hith'n A'CEELfZ.RTVlSiI~ (Skip if only one operation has been "Dillllpl for nach n':tivitv o‘riud-Tunll‘m iwr or nrr0 oncrniion1 nrn pocnihle within s piven artivity port 0d, than thorn may no corriod- o-zt, by tho comrutnr und in actual practice. in a hunter of way: dnpnnlin* on yolr lutor. '1nlrmont, and acrcar- limitations. The ”allowing oxamolo illuntrntns 'Hc t3n4 or infnxnnticn nc‘dodt hsnumo that a {armor has 600 acres (f corn. und that ho has lintnd disCing stalks Ind noldwoord plowin; 'J two oncrstionn that could bu don" in tr» full activity ocriad. Annume furthor that in the czu'xnunt auction(3ccricn ) he li~ts n single tractor for {LII onerntiznu thit cwn dioc stilkw at ”.5 A/hr, and plcu at 2.5 A/hr. Then the computer PPCBV3H Mtdh‘ 51“51”t° 3“” fCIIOani. if “3 WClrJ of ficlf tine worn nvqilatlo ‘lororo ina :rtund frore(.x't21 harvsnt win cnmolcto'l, in fiolda of 317.0: ?03, h A, 35A, 47A, oto. Let I hours spent discing stalks. and ZZZZZ= hours spent plowing. Soounntinl Qggrotions -- ro limits fiunults: Disc 600A ,ru ,)n/\ I 1’93" 1 117.1 L - - . - 0 VA. Wum PIOV 21M ; cornfia] Op:rut'-n~ -- limit ‘C"T"i‘ lflw"" Disc 00A 3 to m} Roguits: [YT/I (in I AI 57A Io...»1..-'n//VJ/fl~f/}mA;;;222?;2;p;22222; P10" 13‘ Concurrént On Arnti Results: Disc 152A ETWJCZ9”K7)T" A EQCQK/ZQQCC/ {ZZZYYZ;IQ’1 JL*LIC/l/YJ> 906/64 L78 Y/QQQOOGQCZK/7IZ' ?low 151A In other words, the computer program may cerform tho various Oper- Activity ’?ricritj ations(tuo or more) in sequence, concentrating your later and nqwip- Period Leq. can ment on ona 30o until it is finicccfi, and than concentrating on tho ,1(}&11)..___... ..4:J noxt job to bo don», etc. Cr it nay oerfcrn the cooracions in an 32(Wintcr) [:1 [:1 arproximutely concurrent manner, so that at the end of the activity """‘ "' period all ororationa pC"€lf1G have been done on about tho none nun— {3(Spr'rg)....... °{:J bsr cf acres. in 9; much as your lfiior. OGH1Dfient. 01’ "CPQHT9 1135”“ '5( est-Emerg)..{:]. 'I:] will nllcw. The comrutnr program TTlhllli that all orcrutionw listed for the planting period on dono uitu Lag concurrnnt modo of operation. You must decide. however, which modo of Operation, a-onentialibsq.) or concur:ent(Con.), GnCJld be usnd in ths other activ- ity periods which hsvo more than ons oparation possible. Check the apprOpriate boxes above. SPECIFIC PLANTING AND PLANTING POLICY INFORMATION Plintina Row Width. Specify the planter row Width. 1-900 th‘ to! width of [::::::]inches Lg"-.— planteru. cultivators and other row-crop OQU1pmentsooosooooo00000000000000.0000- Snoirafl Pie? nrntion For Diwnt‘nv. (S‘Ilp if not r l I :r‘jl"]“L0.T I! ’0‘} 'U1 v0 lrflncd R “tflll Cphl'fltlon Ir t?::aaf?2:: 2:02;:3‘::1..;.;. d in. inznlvin' “‘10 tillaro tc )6 BJn? "r'g‘t b“r°'° ’ YCEZr‘linhn;n;~r c’ scrrs pr“: {:fogz bluntinrj—in attivlt? P"P5°” VU- t‘°“ 7°” ”3' ”n”: :1 ntin c 1‘50 done tn;n on N~03. 'ow to conolvto tuc oclicv statements at the rijht for acgnsfils. a ' “ ‘ '" ‘ c. ‘v'Iv . x 3" P" . ’L9: 02': 21:10 no ... frjzogV’REifitnsplfg:1?E'vugh::e'ad2n0{‘i.ackn y ....rcreat socdbcd preparation field up i‘ . “- )l..-' ‘, AIJ ‘ ’) A~ . ‘ 1 ' U‘ s (11‘ t 11 o planting system, or it may be some nocondnry or( :;0?t i: nii3323~dné¥3uo :113.,..o adoration if‘ you nrxs a :tcra- commntionnl ""1”; tho“ do fld ctr“ ' . ‘ “‘ , ‘ -' .. a. .n 0.00.. tiliu u BSWtPHo hofinrd-'b’v "3L1”3t' th” values instond oercro olnntina. This may rfiylluqtpd M: T336712: ’13 POJRlbulfl 5415.9?! On your ‘39 11 91016 cwvraticn ‘Nflfi'fd only "‘F“V1“‘C“ ‘ith XiJE ”Cils' nntsr V"1"°3 only for thl: purpose, and not normellv “WOPO OPPFCPrlate ior your system. used with your tillage—planting cystcm. n... q- p -5“ (pr F1nntino “nter thn dntos you 5':53;‘nn :6"; 1t. wif soil tenr~ruturo does not 3 influonv‘ your ata?t- or-rinntin; dooiJion, than “hart ”1""t1"” ”° aoonor th°"'[__—_—————J enror tho some data in both boxes. 1f the 3011 tenncr‘Suro has not warm-d-up to 50 b this I dug. I If all tho {inld oonrntions schciclnd to be ”one dntc(nt tho _ -5" an.gh ' chpn 'n activity poriod #l(?prin: Land ?ro*) ”1V6 "Ct dolly pluntinn for awhilo, bcnfi C(3Y.‘,‘1'1Lnd '37! rhC.‘C ’lfltfli). fh!‘ C'lOCk the rut no later thflll....nc.sooosol I Optional no}: of Oporntion which you profer: 209 fjpgg‘ofi_flyhridj Plantgfl. Uae the hybrid type .3 LL? 5T1?» L41: can"; to doucribe your hybrid policy. Use only plant I of a- miny lines as needed. this lhvhrid Noncwhvr. your total mnny : tiP“ CO" ecrtugo will 23 - acres . code Ellfljfl £2 £930 CV9?! ' your by the computer. flrnt : So in years with a "late than 0 cprinq". the lust hybrid " "*”‘— typo listed in the box thon_______L______ will be used to finiah- tn," I up w1th. -————-—-—I——.__‘ .'. . ‘ the“ ' ¢_;;_—fi12.35’”33 . L 3 , urn S”r on hvcri‘ (rejardloss of the 3 = Medium reason 23L. nltnting dates} 1 = ‘ull seaton hybrid a fi . in planter. lHlO is the £19?ilifi.§”1923£2- You mcy(cptional) Specify the sequence or order in which fields should be only field operation [3 To particular planting scquvnce desired. Co to the next sectica. for which this may be 1’92"53Fiht55th........ done. Lil otu"r CDC?‘ Plant this socucnce: ations used to produce [:] Tho cfntuter [::I 41 41 I I I I l-l I ] I47[7 I the CFO? “dill generally S'lC-‘Jld fgllou' IL I 1‘] I 141 T1 I l l I I follow this some order, this sequence... (fielE code nunoars) the. order in which D W'JCTL fields are harvested. 73:_H_‘ Chock the appropriate [:1 1131.;3‘...';R PCSSIaLE, but if the ant field to be planted i! boxes. not tract1ble(cannot bs ucrlcd in) on s given day, the com- puter will scan the rest of the list. If another field is round to be tracteole that day. then plant in it. Return to the next field in the sequence as soon as it dries enough to work in. - SECTION b -- LISTING AVAILABLE FIELD EQUIFHENT AND NEEDED SPECIFICAILONg Each and every piece of field equirnont to be used in producing the corn crop Ihould be listed on the next 2 pages. Use a separate line for each item. Erectors. 0n the folIOWing page. enter a description name (for your use) {or each tractor thhtmlgfiusod in some way for the corn enterpriSc. If a tractor is not used {or field work. but is used. say. for hauling SJPTllfj to the field. for hauling corn at harvest. for run. ning an Lunar at the farmstead at harvest. etc.. then it should be listed. Next. enter a size code ior each tractor based on its rated PTO horsepower (see box). Then enter l fuel type code for each tractor. and the nize of its fuel tank in gallons. laqungngg. Enter a descriptive name fcr each field implement and the appropriate type code from the box. When more thin one unit of a given type is listed, then enter a 'unit number". For inctance. your first planter should be coded as 191 (type 19. unit I1). I second plantvr as 192 (tmie 19, unit #2). etc. Next, enter the.width or size of each implement using the designation illustrated in the box for each. yghigigg. Enter a doqcriptive name {or each vehicle that will be used to haul production Bunrllcn to the field. next. enter {or each vehicle a vehicle-type code. and a unit nuvar (it more than one of the same type). If the vehicle will be used to haul water. or bulk or bapncd fertilizer. then enter the transport capacities requested. For water and bulk fertilizer. enter an estimate of the rate at which these materials can be conveyed or tranaoortei on—to and off-of the vehicle. Give this type of information only for those materials that will actually be hauled by each vehicle. TRACTONS 210 Note -- See equipment code: on the next page. IMPLEWFNT: PC 3' '3') . at A 1124.;pvra :i't I ' 3(u1o s'nl 3 r‘ (1 . H1 7"‘1'; MIL Contln'd 8 '3 ( :11}; {m lennnt r 30 ac as c more space SUPPLY VEHICLES rnnepcrt anacity of Various lxtnrialsxif ueci * 2.fi. 3 Transfer rate 3 fl ‘ J «it r iun" MIR r'ortilizor Tota callons per min bupply JQ1]_:Q% Total :pprx. upprx. ( r; or liquid) Lbs 6: water pound; Pransport loh.fi iiCarriodF.k.In T.R.Out Total T.h.2fi L.R.Cut Bagged per min ’of fort Vehicles I‘vlm' . gal) (ma-Ha (mm-z:- Lbs (Pm-m:- (me Fort, ' ' ' In = Loading material onto the unit at some refill location. Out = Moving material from the unit to field implement or applicator in the field. (Use back if more space is needed) EQUIPMENT CODES "Implement i on Give width or size as: ——~"TU—3‘F%%3Fy Stalk Chopper...... actual width, feet , ll 8 Plail Stalk Shredder...... actual width, feet 35%9t3r 312° C°g%% HP 12 8 Moldhoard Plow............h-bot., lh-inch: etc. 02 ; 50-59 FIFO “P 13 = Chisel Plowoggeooeeoeeeeee actual Width. feat 03 . 60-69 PTO HP 1h 8 Powered Rotary Tiller..... actual width, feet 0h _ 70379 PTO HP 15 - Heavy Tandem Diec......... actual width, feet 05 = 80-89 PTO HP 16 3 Standard Tandem 0156...... aetual width, foot 06 g 90-99 PTO HP 17 g Fiald CUltlvatoro e e e e e e e e 0 actual Width, foot 0? = 106_109 PTO HP 18 2 Spring Tooth Harrow....... actual width, feet 08 = 110-119 pTC Hp 19 8 Corn P1anter..............6-row, 30-inch; etc. 09 : 1?0_209 PTO HP 20 8 Rotary Hoe................ h-row: 6-row: etc. ‘ ’ 21 B Row Crop Cultivator....... h-row: 6-row: etc. Euel T: as 22 I Field Sprayer............. boom length, feet 1 E_3asoline 23 I Dry Bulk Fert. Spreader... spread width, feet 2 8 Diesel 2h 8 Knifedown N Applicator....5-knife, uO-inch: etc. 3 = LP Gas 2538 Nitrogen Nurse Tank....... none xiclen for iro‘wctfcn butnlfé: & HauIin; Cbrn aah‘cle° for .rvductiin buy;liC3 C011 Jvne ’0 EE;;:E] PTO driven Tvu o .‘.-;,‘,ored Feed ‘ unload auger 2—aheel __- r ‘art Trailer ()—J front or back. Frailer rojnction ”sea: t. :1anter. "\ 9 I 1.13 k.- tho tailgate. ..TT"ET [na—-.3vlinp dry Hulr fortili7er to e 7h 0:3lyo-Huulii. rixxle and wupplinu to the planter or other ‘cmnnts, or hauling a watnr or liquid fertil- iunk to Hm I'lf‘ld. ha,3n3d mat- Princinal ” Lf3 72 Fertilizer auger nge II film; ime - 3‘ can be fitted on Flatbed _0' O 4ra\ii.y nagon "’C) - C) either side. «agon Pvuo 1 Fertilizer auger '{325 28 f-nier Dunn can be fitted on Pickup ;iui".it ungon ‘——() h‘ther side. 'Pruck 13173.35 0‘ Hydraulic hoist, 39 {ruck with _ Tortili7cr auger 7Tb” on C] Mrain Bod c'u be fitted to Truck '6‘ Unvfl: All typos-—3 supplies to the planter or to the field. lunlinx ta';ed materials and other implements, hr hauling a Water or liquid Vehicles or beds have no sides, or very short sid3s and tail- 5ate(16" or less). Cartilifur tank 211 germs 5 -- LLLOCATTNO rtqmrmnr for VARIom Piggy; orrni'rioss In this section you must match-up the tractor sizes and individual items of equipment listed in the previous section to for" sluipfign: tots for doinl various field operations. A maximum of 5 equipment sets may be upOTTIfud us veins Eftrntinglx AVuilqhi- for an (peretion. If 3 material is applied with a particular opnrution -— hrrbiztus, isrtiiirar, insecticide, 0.0., then you must also supply information nhout the materials handling system used. with planting you may apply Up to h diffnrnn: matarinls(one of which nmst he need). but with all other oper- ations you may apply a single material only. ELQTrnenE Sets. Wash equipment set snoilJ consist of a tractor plus 1 or P implements. Illustrated below is an “0-99 PTO HP tractor (05) pullinc a moldboard plow(121 a type 13, unit #1). and a 100~100 PTO HP tractortOY) pulling a rotary stal< chopper(lfil) and a tandem disc(lh£). List all equipment com- binations, equipment sets, from your equip- ment inventory that could potentially be used for each field operatiop. .'|<“‘.L with that by entering how many acres wereior could be) covered, a particular field. h3clude any lost tLte for material refills. usual or normal speed of Operation with each nwlipment set. Instructions are given below and on the next page. FIEL‘SSU Feliciti’vn Waite“! . For each equip- set :ive cynical performance figures in so Kany hours of operation, in if a material is appliedJ the operation. than these figures should take place in the field. Estimate the ‘ CR .fifl hYYTfii st. }rc is a a s Sizdfmp n; Many flany F1 laced Codajod Jo: Acresiour Yo ' h‘ Example: i a i )o Example: of No. t1 .‘Io P ) e Veh s eh ‘ In At 0d or a 32_ 1 1‘1, :1 >5 5 r p :erried hate ”ritsi‘Un/A A me — .n ,uo Urco rc True Code nurx 14 eh -—o daterinl Application. (Do only for those ' field—operations where appropriate.) Write a name or abbreviation for the material, then the appropriate code number for it. “ext, indicate the total units of the meter— ial which can be carried by the equipment set, and the application rate in units per acre. Use the same units for the amount carried and applied -- see Hntl Code box on next page. Next. enter a code nunbrr(Natl Supply Source) where the fluid €11£Pfl£fl£ must go to get additional 1upnlle3 for re- fills -- see Matl Supolv Source box. Tn-Fieli Hunplv Vehicles. (Do only if the nnterinl sunplf source for the field equipment is Code 0) A supply vehicle stationed in the field may consist of a tractor with l or 2 trailing vehicles, or a truck with O, l, or 2 trailing vehicles. One vehicle may supply all equipment sets doing a given field Operation, or you may specify a different vehicle for each equipment set. Enter the tractor and/or vehicle code numbers. then a code where the supply 33333;; must be taken to get 9m" 1 1é_9=11r.n.t.1_9r15._.3_*~.3 1:102. ..tlmuuz: 1., e ggkiitional supalies. maximum of S lisss(equipment sets) per operation. #fl In:§ .4 ___ _ clu “glipmcnt r7 .vnical hare ar Materinl e Annlihd Vehicl . .l‘C ‘. S :Oper Sizeimo 0 30: Rod 0 Hany'Many Fldépeedg of A esi'iou 760 )“'.et Uni s fihis Kn fist. “Yams Pfitlifctal Zsrried Applfllrk ..rct s Fate puopflrucKVeh (Un/AlSrc 03 ah 3 Note -- Any material applied with a field oper- htion must be applied with all sets of equipment you specify for that operation and at the same rate. You may use one supply vehicle for all sets of equipment you specify for each field Operation, or a different one for each equipment set, erater Orin in-finld sufply vehicle 519% 3=mslk fort flat; l-h=At a certain fnrmwtend uqqfl_u-'ucged fort iEELll 7=At the nearest farmstead Nos.'5' ulk N Source 0=Dsnler delivers mate ial 6.309d corn ...— JL—lfscnc an off-furm 1.95131: on s be only if the Kati Supp Srce'O for the field equipment. 212 Matl CodquflgL .. .- cnrried by each not of equipment. and gallons per acre applied. 0E3 total pounds carried and pounds per acre applied. in the hoppers. and pounds per acre applied. Use units or actual. but be consistent. and kernels per acre applied. carried and pounds per acre applied. 8 a All Others. a EiiffO Water used for herbicide or insecticide spraying. Uae total gallons 3 - hulk Pertiliggr. Liquid or dry bulk fertilizer -- P. K. starter. pop-up. etc. h - £511 Barred Fertilizer. Starter or pep-up fertilizer. Use total pounds carried 5 - Bulk Nitre'gn. Liquid or ens (NH3) form. Une total pounds carried. either in equipment mounted tanks or in a pulled nurse tank. and pounds per acre applied. 6 - fiocd_ggrn. Use total bushels carried and bushels per acre applied. or total pounds carried and pounds per acre applied. or total number of kernels carried 7 a Dr! Herbicide or Insecticide (applied through a dry applicator). Uee total pounds ail ;upplj Source Judas: gpq~irlaa‘ror Yield fluipgent: gppcifiafi Tor Cuppll Vehicles: 0 = From an in~field iield equipment and Operator supply vehicle-- do not have to leave the field Code 0 not applicable here. which leaves the in order to refill the heppers Use for field equipment only. fld. for matls. or tanks on the equipment. 1-6 8 At the farmstead . A field equipment operator(only (#1 to #6) which one if 2 or more sets of equip- is specified. Field equipment must leave the ment being used), or the man 7 I At the farmstead field and travel to the helping with material refills nearest the fld. location indicated when the must drive the supply vehicle where used. cquipment'a hoppers or tanks to the out-of—‘ield location 11-16 = at the off-farm need to be refilled. indicated when the quantity of location(#ll to material carried on the vehicle #16) specified. must be replenished. Dealer delivers material to the 8 = From an in-field field, either in a transocrt supply vohicle-- Code 8 not applicable here. vehicle he IGBVGS thcrc(nurse which a dealer Use for supply vehicles only. tank or bulk spreader), or he keeps filled. transfers the material into one of vour transport vehicles. Planting Operation: Use a maximum of h lincsimaterials) for each planter. an U n I a Vehicle9 an or on a .a or a s c s s . me a c s Sizolmp Many Many 51 pe of 1 True eh eh. ode e Ac shour o h Hatl 0 Units ' XXX (XXX xx. x xx. x fix? ..v... . alike} 1", .u-ga- XXX (XXX XXX :3 ItXX Note -- If more than 3 planters are to br specified, use back of this page. You may specify a maximum of S planters. ----- 2=Hater =An in-field supply vehicle G De only if the Hatl 3=Wu1k fart Matl l-6=At a certain farmstead Matl Supp Srce=0 ?ode h=uagged fert Supply 78kt the nearest farmstead for the planting 123; 5=3u1k N .Source 8=Dealer delivers material equipment. 6=Sged.corn 11-14=At an off-farm location '“ote -- Any materials applied with one planter must be applied with all planters, at the same rates. You may use one supply vehicle for all plant- ers. or a iifferent one for each. Cr ytu may use one supply vehicle for all materials arrlied, or a different one for each. Note -- You must indicate seedicode 6) as one of the materials applied with the planter. Multiple-Plart~r Options. (Skip if not applicable.) When you specify nultirie sets (f equipment for a partieilar field operation, except for planting, the computer pro'rnm assumes that all the sets Specified may operate in the some field at in) same time. i.e. 3 or more plows, 3 or more cultivators, etc. may all run in the same field together. Check the policy to use for planting: [:3 £32 plnutug‘tg 5 15319 3313. flanters will be allocated to consecutive fields in the plant- inr eequnce, Lh:n s rluutcr fininhen one field. it will be arsijned to the next field in the planting sequence vhich is not occupied by another planier at the time. D 1'92 [jig—litgiu. £2 3.“. L‘J‘l'W liith an iiitfll‘flutl'lg field pattern, one planter will start from uiuh ride of the fixld so that any point rows will ?; in the center part of the field. L 0 All plantero may work together in circular-plante ds. 213 SECTION 6 -- LAHOR FORCE for PRODUCING the CROP The next 5 pages correspond to the 5 activity periods used for producing the crop. Skip these, if any, in which you have not planned to do field operations. The information you must supply! Labor Force Codes. In each activity period Job Priority Codes. Each man should be assigned you may identify up to 10 individuals that FFTEFTties or performing or helping with the might be available for field work. Enter a field operations that can be done during OICH name for each(optional). This Rives each activity period. This is done by entering the one a man(or code) number. Whenever poss- field operation code numbers in the desired ible, you should code an individual with priority positions. The illustration below-left the same code number in all activity periods might indicate the following for man ll: in which he may work, let 12 3 spray herb. after the planter 2nd 110 - help with planter refills 3rd 11 8 run the planter Man #1 would have other priorities assigned for Code each man further by t pen other Jobs in the rest of the activity periods. (Enter in the P/P column 1 - full-time family labor 2 - part-time family labor I full-time hired labor I part-time hired labor The tractor operators for each.field operation will also be responsible for support activities such as equipment maintenance, material refills, getting supplies to the field. etc. For anyone else that helps with these support activit es. the field Operation code number, followed b a zero, should be entered(like code 110 abovei._ e or ~ a un lst 2nd 1rd Work 0 Star Quit Start it Start it Labor Hours , and Job of Priority Labor 10 Labor Work Schedule. Indicate the otential daily hours of field work for each man by entering starting and quitting times in the don-rri columns. Circle 3 for AM(or cross—out 2) or 2 for PM(er cross-out a) with each entry. For Saturday or Sunday work use the following: a) Check the box at the top. nothing else. The computer will use the same hours as for Hon-?ri. b) Check the box, enter times only for those men that work different hours on the weekend. The computer will use the same hours as for Mon-Fri for all other men. c) be not check the box at the top. Enter the times for all men that could work on the weekend. Activity Period #1 -- Pall Land Prfipflrfltion Job 1 1: Codes Fields Code a - arves o ne- - arves n 3 Operation No. 0 N t st 2nd rd # # Egt1_l -— Enter 3 for harvest in this ‘ -column(lesve other # columns blank) for # those men, if any, that will be busy with harvesting activities, and not available for land preparation jobs until after harvest. MThis table for your use and convenience-- it is not part of computer input. Labor Work Schedule: Mon-Fri Sat Sun 0 Sta t it Star ‘uit Sta t [otg_g -- As long as corn from last year's crop remains to be harvested, the Labor Work Scheduleihours) which you specify in the harvest section will take precedence over the one given at the left here. -<— Note_1 -- For those men with priority fl above, if any, enter the potential hours of field work for land preparation activities only, i.e. to be applied after harvest has been completed. 211+ Agtivity_?eriod [2 -- Winter Land Prep Job Priority Codes ' Fields Code “fiTs / - rvest 0 one: ‘InREGEh n s Qperation No. Name st ?nd st _.-J 1? fiThis table for your use and convenience-- it is not parj of computer input. 0 Labor Work Schedule: Mon-Fri Sat it Sta t Note 1 -- Enter K Tor harvest in this column(leave other columns blank) for those men, if any. that will be busy with harvesting activities, and not available for land preparation Jobs until after harvest. Note 2 -- As long as corn from last year's crop remains to be harvested, the Labor Work Schedule(hours) which you specify in the harvest section will take precedence over the one given at the left. «e- Note -- For those men with priority 3 above, if any, enter the potential hours of field work for land preparation activities only, i.e. to be applied after harvest has been completed. Activity Period #3 -- Spring;iPre-Plant) Land Preparation e G 0 Operation No. PThis table to your use and convenience-- it is not par of computer in at. Labor Work Schedule: 1 Sat it Start s o t Sun t Start Note -- On the first day that planting can be done each spring. the Labor Work Schedule you specify on the next page for the planting period will over-ride the one specified at the left.‘ The same is true for Job Priorities. 215 Activity Periodyfik -- Planting Period Piilfii“’F33§ n 0 Operation lo 0 Name Note -- If the planting operation itself was not restricted to cer- tain hours in Section 3. then you may want to enter longer hours (or Sunday work) for certain men if planting were still going on in late May or early June. LL mThia table for your use and ‘ convenience-— it is not par of computer -392254____. A labor work schedule for the middle period below(May 3-Hay 23) must 23 filled-in.‘ The other two periods are optional. Labor Work Schedule: Planting GEFORE May 3 Planting May 3-May 23 Planting AFTER Kay 23 Mon~Fri Sat Sun tart 'ui tart i tart .a Mon—Fri Sat Sun Mon-Fri Sat Sun *t rt 1 tart ’ i tart 'ui tartvg‘ui~ tart i tart i n Lgtigitl‘figgiod #5 -- Post-Emerge(Tendingz Period ‘ P151311» '30:. .a .an s 0 Operation 0 N st I I tThis table fofi your use and convenience-- it is not par of computer input. Labor Work Schedule: Mon-Fr Sat Sun 1 Start t Start Note -- This Labor Work Schedule will stay in affect each year until all field oper- ations planned have been completed, or until all corn reaches layby height -- whichever comes first. 216 floove .wCAveOAd: “one no omnonu:cov e. o>e o. mood.o an aa..sou unflaausoMu-w wade: manhuaucoo . a . . choc N o: uo amouo>e yucca ee .59 .xoauaonnnc mu gunned temc.amu .‘ouuanpoa muacu m uo Edeuxofi annrunnco me4annopanufiem a no.m m:r«mm~ NN snub .orunosuou nosfla> nonuo or» “no .nonn on o» oCanKoo some Lou are: o>fipafiaonop m poucm arcaumuauuuoaw can mocunfioo .wopoo: u“ ”more Eon» hausvvaouu on» c“ uso uofloano> podm,nu .hnco ”Head on» we acco on» us noaoaso> ponm flu "Abouneauunaasoauo uoc one can» npaoau Louvxoc oco xcezo .caoo abandon a» ncflounm> uponncaau noon on woo: pea pouscaoo esp .ooceoc Con: pfloau as» ea etnenue>a one nonuflze> cc: henna ua mcfipucars oonmzeuzo an: flu .Aue. rrauu taco wraazc vocacue schnzoovhaco we’reoac: moem on: mm .6093 on an mcupeofics he can» ezu 300:0 accuuqonmcacccac: xccfi :«eau .uoCannoo uou eao>aap moaaoa as o>uon has one .onau nounuaeou nomumno on ace and: .ec«nfioo on» mean. an «no no“) and non .nouuasauos menuno>aen no“: pesao>5a son a Isaac-easeseeeeaeeeeefldflu puma ”0056165 hflHGGE H0.“ 05" ”HGH , .uouahono no“ one aaanaoo as» o» compose on «an: nounran on no and» cap“ as .vanea uo>o no: ma nn>«ac uoaaou a c up one .nunu house so» «H .ofiau fines pa AnVoCHnEoo on» no>o nose» tendon uoaaou a awn» concave“ Hafiz nauseaa duo manuoucm .n« as no»: on ”Man ”aqua nonvnomuafl no nopscas m nu scan: open amuse ooh 05He> .u< .emouaa ononu us mnauehego ma rm r one soon NH pa acumnflaon 4 you hounuuoo on» hp noaupvxoc on HHax mucumatao aflonu pas nonuneoo ”Hoax too easy oHcH «cannon .uous econ: efiowu on» _ fi.....uaoaaceuu aeu been abouoeuu aoaeec .vuaaaeu on» uu .vens open: .mHu ecu cmuo .nouou coapaoo _ w........naouoeuu ere nonunuoo uo senatoucuen use mcuaosuom .houfloa use» you once codueooa ecu noucm .wnuumuuat e as no nflcfiu ecu c“ on has used mafianen you poms nuance. pun nmc.nnoo on» do o'cqum ace_ch>c cam mrhaosuoa .mco. ouu rescues «Cauuom acouumoon unnrm awm unoum .poms on pmwh % AH opoovneouunu naasou4o a pact: ..asoaa emucsfia lunwnosau poo oaonaan>m uoc nepouumn omenmu m women ,FV .:.r:wc\ onepuqn vwcu MHHHHf........pons on o» cucuuma uwnfiu or» up rtn.rJr vvoo on» nourm ubouam‘uopcmp ”Mn f...........ueuus no co herhca mauuec>aan rwmon Cara .zca nan» uow u.¢aoop easpnaoe argues um 00.8 B.eeaeeaeeeeooeuoeeeou Clem» QUOM BCOuCOU Qfiflunuoan H0Ch$8 Con: enoapon ads» you Mauunopaen cumrm "cusp «sauna»: huoumpcefi a use eaduuaofi meauasue confine» ecu ucucm .hce on .ounuauno>ang us Euounuuo veroB no Etsuuco voahc on ou Chou Lou anon mace ouennvoo mucosenandom ncauaeum M Lawn . . 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When developing input for the model. the user describes each field in terms of the field section(s) of which it is composed. At that time each field section represents a portion of the field that can be geometrically described (or approximated) by a base rectangle with an upper and lower triangle modifier. Figure Cl. presents the basic properties of a field section. and illustrates the various shapes that a particular section may possess. When the user is developing input. he must number the field sections in a given field from left to right. The section origin of the lowest numbered section in each field (the leftmost section origin) is designated the field origin. The field origin is point (0.0) for the x—y coordinate syStem for that field. Note that the x-coordinate of all points in the field is non-negative. while y-coordinates may assume any value. The x-coordinate of the section origin of the Kth section is k-l in . particular field. and K:>J. The y-coordinate of all section origins in a given field must be supplied by the user --in addition to the properties L. W. HU and HL shown in Figure 01. N1, where J is the lowest numbered section in the An additional field section property may be specified by the used: the location and size of no-till strips. A no-till strip is an area within the base-rectangle of a field section in which planting. harvesting and other field operations can- not be performed, i.e.. it reduces the effective row length of the section. Two types of no-till strips were identified: type 1 -- those through which field equipment could travel -(but not ”operate"), and type 2 -- those which could not be traversed by field equipment. A maximum of two no-till strips of each type may be specified for each field section. The specification for each requires two numbers: the vertical distance from the section origin to the lower edge of the no-till strip, and the amount by which the effective row length is reduced. 233 W.L = upper triangle modifier I HU base __ rectangle.“ix ‘ -‘—-wr—a- HU.HL = section L origin ‘ HL lower __1. triangle modifier Width. length of the base rectangle. where L s O, W’) 0(always). The lower-left corner of the base rectangle is defined as the section origin. Height of the upper. lower triangle modi- fiers. Area of the section is the area of the base rectangle plus the areas of the tri- angle modifiers -- posi- tive heights add area. negative heights sub- tract area. a) Basic field section properties. HU HL "V 0 HU‘) O 0 HL > O RU > 0 HL > O c) Sample field section shapes with L = 0. Figure Cl. Field Section Properties and Alternative Shapes. 234’ Given this field section information for each field, and the field size (in tillable acres), initialization sub- routine FARMI is designed to reconcile any differences that may exist between the given tillable acreage and the field area as computed from the section dimensions (that are taken from a scale drawing of the farm). This is done by expanding (or contracting) each section in proportion to its area and that of the whole field in which it is located. During this reconciliation process, the x-y coordinates of field entry points (supplied by the user) are alSo adjusted appropriately if need be. A field entry point is a point, located somewhere on the field boundary, at which entry to the field (with field equipment) is possible. Two types were identified: 1. Principal field entry point -- Field entry at this point is from a farm lane or public road (either gravel or paved). 2. Secondary field entry point -- Field entry at this point from another (adjoining) field. Every field on the farm must have a minimum of one entry point, either principal or secondary. A principal entry point has three attributes: its x-y coordinates and the number of the field in which it is located. Secondary entry points always occur in pairs. Each has four attributes: its x-y coordinates, the field number in which it is located, and the adjoining field number.* Following the area-reconciliation process, subroutine FARMl partitions the whole farm into 100 smaller field sections of approximately equal size. With each field, two partitioning techniques are possible, depending on the field pattern which the model-user intends to use for planting, which must be supplied as input. The two techniques are illustrated in Figure CZ, and proceed as follows: 1. Alternating planting pattern intended. The original field sections are simply partitioned into a whole number of smaller, standard sections using the nominal section area that will produce 100 whole sections on the farm. In this type of field, planting must be * Actually, when FARMl reads the field-field entry point infor- mation from data cards, it sequentially numbers the principal entry points and the secondary entry points, and stores, in the x-array, as an attribute of each field, the lowest and highest numbered principal and secondary entry point for each fields 235 a) Field and field sections to be partitioned. field origin b) Partitioning field into 7 standard sections of approximately equal size. field origin l/;f' ‘\K\1E. new section origins /A\ 1 I I l c) Partitioning : field into I 7 circular I sections of I I I I I I J L1“ f equal size. L C r! \ 'L Ni I W 'F I I I I I I I I I l L f u— new section origins \‘ origin !:," \‘ saga: -’7 v‘ A S l). T Figure C2. Partitioning A Field Into Smaller Sections. 236 performed with the continuous alternating field pattern. but other field operations (tillage. cultivation. harvesting. etc.) may be done with an overlapping field pattern or with a land field pattern of some type (See input form in Appendix A) as specified by the model-user.* 2. Circular planting pattern intended. The field is assumed to be a rectangular field of the same size as the original, with a width and height approxi- mately the same as the original field.** The entire field is then partitioned into a whole number of smaller. circular sections using the nominal section area that will produce 100 whole sections on the farm. In this type of field. planting and all other field operations must be done with the circular field pattern. Though circular field patterns are not permitted with the present model. subroutine FARMI is operational for circular section partitioning. With circular field sections. H0 and HL are always zero. the section origin and section width (base rectangle width)are as noted in Figure CZ. and the section length (base rectangle length) is stored in the x-array as the composite number AAABBBB.BB. where AAA is the length of the vertical side of the section directly above the section origin (to the nearest whole rod). and BBBB.BB is the total outside (circumferential) length of the section. The x.y coordinates of all field entry points are also adjusted to put them on the new field boundaries in the same general location they were in with the original field shape. The y-coordinate of each circular section origin is stored in the x-array (as with standard field sections) though it. as well as the x-coordinate of the section origins. can be determined by the section widths. *Use of a field pattern other than the continuous alternating field pattern is not permitted with the model in its present stage of develOpment. *“A rectangle that will enclose the original field is first established. It is then shrunk until its area is equal to that of the original field. APPENDIX D 4sz 237 APPENDIX D ACTIVITY STATES PROPOSED FOR THE FILE ll ENTITIES ASSOCIATED WITH ON-PARI DRYING Type of Activity Entity State No.’ Type of Activity Dump Pits and Inactive (empty. partially filled. full). Holding Bins Corn inflowing only. Corn outflowing only. Corn inflowing and outflowing. NN.-e Conveyors l Non-operate or idle. 2 Operate or non-idle. Dryeration i Inactive (empty). Bin 2 Corn inflowing only y. a Temporary held during filling (bin is non-empty). Cooling plus corn inflowing. 5 Cooling only. 6 Temporary held during (or at the conclusion of) cooling. 7 Corn outflowing by gravity (free-flow). 8 Tempraxy hold during gravity outflow. 9 Corn outflowing with bin sweep. 10 Temporary held during mechanical outflow. Batch-in-Bin 1 Inactive (empty). Drying Bin 2 Corn inflowing only. ‘3 Temporary hold during fillirg(bin is non-empty). u Drying plus corn inflowing. 5 Drying only. 6 Cooling only. 7 Temporary hold during drying or cooling. or at the :oncl-:ion of the drying-cooling cycle. 8 Corn outflowing by gravity (free—flow). 9 Temporary hold during gravity outflow. 10 Corn outflowing with bin sweep. 11 Temporary held during mechanical outflow. Portable Batch Drier Inactive (empty). Corn inflowing only. Temporary hold during filling (drier is non-empty). Drying only. Cooling only. Temporary held during drying or cooling. or at the conclusion of the drying-cooling cycle. Corn outflowing only. Temporary held during unloading (drier is non-empty). O‘I NNNH Continuous Flow 1 Inactive (empty).. Drier 2 Corn inflowing only (at the start of the season or s new drying period). 3 Temporary hold during filling (drier is non-empty). h Drying (and cooling). corn outflowing (and inflowing). 2 Temporary hold during drying. Corn outflowing only (at the end of the season or this drying period). 7 Temporary held during unloading (drier is non-empty). Dry Corn Storage % Inactive (empty. partially filled. full). Site Corn inflowing only. 3 Corn outflowlng only. * Values that the HST-attributes (in Appendix B) may assume during activity-simulation. APPENDIX E 238 APPENDIX E COMPOSITION OF THE GASP EVENTS FILE FOR REAL EVENTS For a one-man harvesting and handling system (without on-farm drying) the entries shown in Figure E1 were required -- see Table 6 for additional information. Note that floating-point attribute cells 9 through 15 were not required for any real events. In fixed- point attribute cells 2 through 7. ID indicates the entity-ID in- formation for the entities directly involved with the specific event. These include: NSET(2) - an operator (man) in file 6 NSET(3) - a corn delivery point in file 11 NSET(u) - the harvest field in file 10 NSET(5) - a tractor (if any) doing farmstead work in _ file 11 NSET(6) - the combine in file 7 NSET(7) - a transport set in file 8 Entity~ID information is stored as AABB. where AA is the GASP column number. and BB is the GASP file number. Blank cells (2 through 7) will usually contain the designated entity-ID informa- tion. if it was available when the event was scheduled. even though the entity may not be directly involved with the event. The values in fixed-point attribute cell 8 designate the following: 2.3 = normal-pattern harvesting activities are continu- ing: 4.5 = end-of—the-day (season) -- all activities now aimed at moving equipment units to their overnight (long-term) storage locations. 1339 i!- meant! r. . ...h. .u . .e_.le..h.r.. .11.. .w-r .mpsosoewddom evaneavp< pso>m Hamm .Hm .asmem n.~ «ewe m.~ m.~ «ewe m.~ m.~ aeez aeez «ewe m.~ mz.o mz mz mz m QH oH - oe - - -- me 2H - - me mzez oH - e me - me me me me me me me -- oe - Nzas neme - o - - - - - - - me QH me - I- - - me n - - - I- - me - - - - - - - - I- e - - - - - - - - - - - - oH me me n me - me me me me me me me me me me me me me ~ Hm om as we we as me me as ea e m e m m advemmz - I- - - - mzo< - - - - - - - - - m ozze - - - - uses - - - - - - I- - - e some - I- - - eo>z - - - - - - - - - p smze - - - - zm>z - - - II zone zmze - - - m ezze - zmze 3mze - zmze zmze eeem - - zmze zmzz - - - e ezzx - zmzx zmzx -- zmzz zmzx Seem - - zmzx zone - I- - m aqoe mace oaoe mace mace once mace mace mace mace qgoe oqoe once ence mace N zmze :mze zmze zmze zmze. zmze zmze zmze zmze zmze zmze zmze zmze zmze zmze Assemm mmemezm ezmsm Heoo 240 . I. . «I {Item Ia z.e.eeo.s.em onsmee “.3 n.: “.3 n.~ Q... n... as - - n.“ - - m ae an an II oH -- II -- me me me me nu me e - - - me me me nu me me - - aH - - m neee - II I- - I- - - - - - - o o m - - - - - - - I- I- - - - - - a II me II II II II II II II me me II me an m me oH me me me me an me me me me me me me N on mm an em on an en mm on on ma ea ea we szemmz - - I- - II mzo< mzo< mzo< -- - - - - - m - - I- - ozze ozzz ozzz oz>z - -I - eeze - - e - I- II - some ao>z eo>z mozz - - - eeze II _ - w anon -- seem mace zmze smez seem zmzz zgae - - zgqe - - m zmze ozze - gaze - zmze zmze zmze zmze ozze I- zmze came - a zmzx same - zwze -- zmze zmze zmze zmze smee seem. zmze zmme ezzo n 58 See 52. 32 See 38 See 38 See 32. See 38 38 38 N gaze zmze smze zmze zmze zmze zmze zmze zmze zmze zmze zmze .zmze zmze Svemma mflHmazm azm>m HHoo ACRE 0... CODE .... rams .... FLDN .... HVBU .... aver .... uvmc .... ID .0.... IPIL .... ISTA .... MANi eeee NS 0.0... NTYP .... OMKT .... RTIM eeee STAT .... 2A1 ATTRIBUTE DEFINITIONS Acres harvested during this activity. Location code (1-30 = field 1-30. 101-106 = farm stead 1-6). Farmstead number (1-6). Field number in which the entity will be located. Bushels of corn harvested during this activity. Cubic feet of corn harvested during this activity. Moisture content of corn harvested during this activity. Entity-ID information for the man (cell 2). delivery point (cell 3). harvest field (cell 4). farmstead tractor)(cell 5). combine (cell 6) or transport set 0811 7 e Filing indicator (0 = this transport set will not be gegded today. i a it will be,file a dummy event for t . Activity state of this entity for its next activity. The termination of its next activity has already been scheduled (an event filed). Zero. or the entity-ID information for a second. third (i = 2.3) man assigned to assist with the activity. Special start-of—the-day activity indicator. Type of activity inteuupted by this repair activity (1 = unloading a transport set at a high-moisture silo. silo-tractor repair. 2 = transport set travel. 3 = grain handling. conveyor repair. 4 = drying or cooling bin operation. 5 = on-row combine operation. 6 = portable batch or continuous flow drier operation. 7 s on-row tractor and implement operation. and 8 = on-the-go combine unloading). Off-farm market number (ii-16). Accumulated hours of use until the next repair of this type will be needed. Activity state to which the transport set is to be re- turned (NTYP = 2 only). See attribute NTYP. TNEW TOLD TRBU TRCF TRMC XNEW .... XNXT YNEW YNXT 242 Time of occurence of this event. Time at which the entities associated with this event last changed states. Bushels of corn transferred from one entity to another. Cubic feet of corn transferred from one entity to another. Moisture content of corn transferred from one entity to another. New x-coordinate of the entity. X—coordinate of the next start-harvest point. New y-coordinate of the entity. Y-coordinate of the next start-harvest point. LIST OF REFERENCES REFERENCES A.S.A.E.. 197a. Agricultural Machinery Management Data. ASAE Data: ASAE D230.2. Agricultural Engineers Yearbook. American Society of Agricultural Engineers. St. Joseph. Michigan. Barnes. K. K.. T. W. Casselman and D. A. Link. 1959. Field Efficiencies of u-row and 6-row Equipment. Agricultu- ral Engineering #0:1h8-150. Fridley. R. B.. 1971. Simulation of soil freezing. soil thawing and soil temperature for use in systems ana- lysis of corn production. Unpublished report. Depart- ment of Agricultural Engineering. Michigan State University. East Lansing. Michigan. Geyer. F. P.. 1963. Systems engineering analysis of mater- ials handling on Indiana corn-hog farms. Unpublished M.S. Thesis, Department of Agricultural Engineering. Purdue University. Lafayette. Indiana. Herum. F. L.. 1962. Specific volume of shelled corn. Un- published report. Department of Agricultural Engineer- ing. Purdue University. Lafayette. Indiana. Holtman. J. B.. L. K. Pickett. D. L. Armstrong and L. J. Connor. 1970. Modeling of Corn Production Systems - A New Approach. ASAE Paper 70-125. American Society of Agricultural Engineers. St. Joseph. Michigan. Kepner. R. A.. R. Bainer and E. L. Barger. 1972. Principles 9: Farm Machinery. The AVI Publishing Co.. Inc.. West- port. Connecticut. #86 p. Manetsch. T. J.. 1969. Design. Development and Use of Simulation Models for System Planning and Management- Paper presented at North Central Regional Farm Manage- ment. Extension and Research Conference. Michigan State University. East Lansing. Michigan. October 13—16. McKibben. E. G.. 1930. Some Fundamental Factors Determin- ing the Effective Capacity of Field Machines. Agri— cultural Engineering 11: 55-57. 243 244 REFERENCES (cont'd.) NaYIOrp To He. Jo Le Balintfy. De Se Burdick EHd Ke Chu. 1966. Computer Simulation Techniques. John Wiley & Sons. INCe. New York. 352 p. Parsons. S. D.. L. K. Pickett. J. B. Holtman and R. B. Fridley. 1971. Modeling Man. Machine and Crop Re- lationships for Corn Combine Simulation. ASAE Paper No. 71-627. American Society of Agricultural Engineers. St. Joseph. Michigan. Pritsker. A. A. B. and P. J. Kiviat. 1969. Simulation with GASP II -- A FORTRAN Based Simulation Langgage. PrentIEe-Hall. Inc.. Englewood Cliffs. New Jersey. 332 p. Renoll. E. S.. 1966. Machine Capacity and Efficiency as Influenced by Field Geometry. ASAE Paper 66-672, American Society of Agricultural Engineers. St. Joseph. Michigan. .. 1969. Row-Crop Machinery Capacity as Influ- enced by Field Conditions. Bulletin 395. Agricultur- ai Experiment Station. Auburn University. Auburn. A abama. ___.. 1970. Some Effects of Management on Capacity and Efficiency of Farm Machines. Circular 177. Agri-' cultural Experiment Station. Auburn University. Auburn. Alabama. .. 1972. Concept for Predicting Capacity of Row-Crop Machines. Transactions 9: the ASAE 15(6):1028- 1030. Sammet. J. B.. 1969. Programming Languages: Histogy Egg Fundamentals. Prentice-Hall. Inc.. Englewood Cliffs. New Jersey. 785 p. Stapleton. H. N. and K. K. Barnes. 1967. Data Needs for Agricultural Systems Analysis. Transactions 9;,thg ASAE 10(3): 303-309. Stapleton. H. N. and W. W. Hinz. 1974. Increase Farm Profits Through Better Machinery Selection. Bulletin A-78. Agriculutral Experiment Station and Cooperative Extension Service. University of Arizona. Tucson. Arizona. ‘ Tulu! Me Ye, Jo Be Holtman. Re Be Fridley EUd Se De Parsons. 1973. Timeliness Costs and Available Working Days -- Shelled Corn. ASAE Paper No. 73-1531. American Society of Agricultural Engineers. St. Joseph. Michigan. 2II5 REFERENCES (con'dI) Von Bargen. K.. 1968. man-machine Performance in a Baled- Alfalfa-Hay Harvesting System. Transactions 9; Egg ASAE 11(1): 57-60.6u. ' .. 1970. Analysis and simulation of a field machIne and transport system for row-crop planting. Unpublished Ph.D. Thesis. Department of Agricultural Engineering. Purdue University. Lafayette. Indiana.