Tue, Jul 17, 2018
5:00pm to 5:40pm
Increasingly thin profit margins require farmers to strive for efficiency in all aspects of their operations. One of the most expensive pieces of equipment farmers own are combine harvesters. Redundant travel with these machines is costly to farmers, so increasing in-field efficiency is important. Currently farmers rely on experience to plan harvest routes and minimize combine idle time. Variable field conditions and yields, and irregular field boundaries, make this task extremely challenging. The goal of this research was to create a harvest logistics model capable of minimizing in-field travel for both combine and grain cart, as well as increasing overall field efficiency. The model was created in MATLAB that used the Genetic Algorithm to optimize the in-field travel. Data was collected from two producers totaling ~3600 acres. Planter shapefiles combined with header width were used to create the harvest passes. Validation data was collected from both the combine and the grain cart that provided location and machine parameters on a 1 Hz interval during harvest operations.
John T. Evans IV
Grew up on a diverse farming operation in central Kentucky that produced corn, soybeans, beef cattle, sheep and tobacco. Graduated from the University of Kentucky with bachelors and master’s degrees in Biosystems Engineering with a focus on Machine Systems. Currently concluding a Ph.D in Biological Engineering at the University of Nebraska-Lincoln focused on grain harvest logistics modeling and optimization. Will start in late fall as an assistant professor at Purdue University.