NETWORK SIMULATION OF CROP HARVESTING AND DELIVERY FROM FARM FIELD TO COMMERCIAL ELEVATOR

This study focused on developing a system simulation model representing the logistic issues related to grain harvest, transportation, receiving and storage in the supply chain around a local commercial grain elevator. The investigation focused on the grain flow during harvest directly from fields to on-farm grain handling facilities and from fields to local grain elevators. One aspect of the model evaluated field harvest and field-to-farm traffic. In the model, the distances from farm storage to field (actual combine position) was computed, and the on-road vs. in-field distances were distinguished. This distinction allowed for different speeds for off-road and on-road traffic, as well as travel with and without a grain load. Alternatives (combine size, field and farm sizes, information technologies) for improving grain harvest and transportation from field to farm, and the impact of weather conditions and yield variability on harvest operations were evaluated. The model was verified and then applied to different harvest day scenarios. In one simulation experiment, the transportation capacity was sized based on a class VII combine harvesting 2560 acres. The maximum predicted field efficiency was 92% when three 850 bu grain carts were available versus 82% with only two 850 bu grain carts. A second aspect of the model evaluated grain transport from field to elevator. In one simulation experiment, nine large farmers with 11 combines delivered 25 loads each to a local grain elevator. A comparison was made for the use of 22 trucks versus 31 trucks to serve the 11 combines. The total time to deliver 225 loads/day was reduced by 25% (1189 vs 948 minutes) when 40% more trucks were utilized. The average service time at the elevator for each truck was 11.8 minutes (22 trucks) vs 12.7 minutes (31 trucks). System simulation as described above can be combined with economic analysis to improve overall elevator receiving performance in light of increased farm field and equipment sizes as well as crop diversification that require identity-preserved segregation and tracking.