Development of sensing and processing technologies for optimal portion control in an automated can filling system

This thesis investigates the problem of portion control of natural objects such as fish and meat for packaging, and develops a new method for optimal portioning. Food portions that are processed for packaging or canning should be optimized with respect to a specified "target" portion, for reasons such as wastage reduction, regulatory requirements, consumer appeal, and aesthetic considerations. The approach of optimal portion control that is developed involves cutting a set of objects into pieces by taking into account the weight distribution of each object and grouping the pieces into package portions according to a weight-based optimality criterion. First, a general optimization model is developed for the portioning control problem. Next, the model is made specific to a practical and innovative approach for can-filling of fish. An optimization model is developed for the portion control of fish where the objective is to minimize the weight deviation of the canned portions from the target net weight of a can. The portioning process is then refined by incorporating realistic assumptions and constraints that exist in industrial fish portioning processes. The modified model is further checked again for feasibility, and the model refinement process is continued until a feasible optimization model that can be implemented on-line in an industrial plant, is achieved. The model that is developed in this manner provides a computational speed for portion control that is consistent with the typical industrial requirements of the process speed and filling accuracy.

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