A discrete event simulation model for analysis of farm scale grain transportation systems

Grain transportation from the field to an on-farm storage facility is a critical component of the harvest system. A discrete event simulation model of grain transportation was developed to evaluate how truck and driver resource constraints impact material flow efficiency, resource utilization, and system throughput. Harvest rate and in-field transportation were represented as a stochastic entity generation process, and service times associated with various material handling steps were represented by a combination of deterministic times and statistical distributions. The model was applied to data collected for three distinct harvest scenarios (18 total days). Wheat and corn harvest from a large Kentucky operation was selected to evaluate the effect of different harvest rates (in wheat and corn), and corn harvest from a smaller Michigan operation was used to assess how the model handled situations where a single operator shuttled multiple trucks. The observed number of daily deliveries was within ±2 standard deviations of the simulation for 15 of the 18 input conditions examined, and on a daily basis, the median error between the simulated and observed deliveries was −4.1%. This model can be used to simulate how changes in vehicle and labor constraints impact the overall system performance. An important extension of this concept is that, given an existing equipment set and labor force, a producer can estimate how often grain transportation is the system bottleneck and simulate the impact of additional vehicles or labor on grain transportation efficiency.