Applying the machine repair model to improve efficiency of harvesting fruit

Harvest costs are generally the single greatest expense for specialty crop producers. Identifying and reducing inefficiencies during harvest are essential steps towards reducing costs and maintaining product quality. To streamline harvest operations, the number of workers and machines required to harvest, handle, and transport the product needs to be planned along with the execution of field operations. In this paper the fruit harvest and the bin collection process are modelled, adopting a modified machine repair model (machine interference problem) from the operations research area. An algorithm was developed in Matlab® to evaluate the performance of the system and improve confidence in sizing the fleet (workers and machines). Two different case studies are modelled using this algorithm: i) manual table grape harvest in Greece, and ii) manual sweet cherry harvest in Washington State, USA. First, the harvest procedures are described, and then the machine repair model is formulated to model each process. The bin loading process during grape harvest in Greece, and the sweet cherry picking process in USA are simulated. System performance under different number of bin carriers (or pickers) and loading stations is evaluated and results are presented.