Abstract
Recent developments in food consumption open up new challenges in production control in manufacturing systems with low levels of automation. The demand for fresh and healthy products, in combination with the demand for processed products, requires short throughput times and attribution of exposure to process-specific, time-sensitive negative quality influences on certain products. Therefore, this article presents a framework incorporating quality aspects into production planning and control by developing mixed-integer linear programming for scheduling and integrating it into simulation-based control for sequencing. The article applies this framework to a flexible job shop problem derived from a real-world use case. The resulting schedules are used in a simulation model using different order release schemes and priority rules to test how the scheduling approach could deal with dynamic manufacturing environments. The evaluation shows the satisfying integration of quality issues in a flexible job shop problem by minimizing the deterioration while not compromising on makespan and utilization.
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