Optimal Field-Bin Locations and Harvest Patterns to Improve the Combine Field Capacity: Study with a Dynamic Simulation Model

Grain harvest has to be done in a timely manner, in order to harvest the whole farm within the available suitable weather days for the operation. This short period combined with an increasing farm size, has lead farmers to buy more expensive combines with higher theoretical harvest capacity. A bigger combine does not automatically imply higher capacity. The grain harvesting process involves the operation of a system of machines, ,as a result, the field efficiency of the combine could be limited by the capacity of the transportation or the temporary in-field storage systems. A discrete event simulation model could take into account this complexity, simulating the operation accounting for field size and shape, field distance to silo, yield and resources available. With the aim to optimise the grain (wheat) harvesting and transport operation, the authors built a discrete simulation model. This paper will describe the application of the model to determine the optimal field bin allocation for a wheat harvesting system in South Australia, for fields of 70 ha average size and average yield of 2 t.ha and 4 t.ha. The cost reduction and energy savings are noticeable, with positive effects also on the environment. Considering 3000 ha of wheat with the yield of 4 t.ha, owned by a single farm, scenarios B and D allowed for a reduction of 246 h vs. scenario A per season in harvester work (45%). Besides the saving for the farmer, this relates to roughly a 5600 kg reduction in fuel consumption, that yields a reduction in CO2 emissions of roughly 15.5 t.year. The model can be applied to a real farm since every harvest pattern in the field is represented as a series of linear segments. In this way the shape and the field conditions could be represented very well in the model.