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The 2011 ASHS Annual Conference

7133:
UML Modeling of Mechanical Harvester Work Flow

Wednesday, September 28, 2011: 8:00 AM
Kohala 4
Yiannis G. Ampatzidis, Center for Precision and Automated Agricultural Systems, Washington State University, Prosser, WA
Matthew Whiting, Horticulture and Landscape Architecture, Washington State University, Prosser, WA
Xiaoquang Du, Center for Precision and Automated Agricultural Systems, Washington State Univ, Prosser, WA
Qin Zhang, Irrigated Agriculture Research and Extension Center, Center for Precision and Automated Agricultural Systems, Prosser, WA
Various forms of mechanical harvesters have been developed for different fruit crops with the general goals of reducing harvesting costs, improving harvest efficiency, and increasing profitability. The development of a novel harvest system must address key challenges including: variability in canopy architecture, large dense canopies, uniform fruit removal, potential yield reductions from uncollected fruit, and fruit damage induced during detachment and/or collection. Our lab group has been investigating potential mechanical harvest systems for sweet cherry (Prunus avium L.) and addressing these important factors. We have reported previously on a prototype mechanical harvest system that utilizes a rapid displacement actuator (RDA) in a modified ‘shake-and-catch’ procedure. The current report describes recent efforts to improve and/or redevelop this mechanical harvesting system by modeling all activities and states of the harvester during actual and simulated harvest. The main harvest system components will be described and the utility of each component outlined. Further, a model describing the work processes of the harvester will be presented. The model is developed using the state diagrams of Unified Modeling Language (UML), to explain how the main harvester components transit from state to state dynamically. Using these state diagrams the behavior of an object (response and action) can be predicted through the entire system. Inefficient steps in the harvest process will be identified from a multitude of sensors (e.g. pressure transmitters for monitoring of hydraulic system pressures, accelerometers, RTK GPS) on the harvester to capture the time spent in each state during harvest. Finally, recommendations for the improvement of the harvester components will be presented based on the work flow analyses.