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Joint optimization of preventive maintenance plan, production schedule and quality control policy in a discrete manufacturing plant

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In the past, operational policies of a manufacturing plant involving production scheduling, maintenance planning, and quality control have been decided independently. However, since there exists interaction effect among the three aspects of operations planning and since the effects can inform managers about their manufacturing performance, joint consideration of policy involving scheduling, maintenance planning, and quality control is an important area to be investigated. If the effects can be jointly optimized, managers can decide which aspects they need to focus on in order to meet requirements such as high product quality, low manufacturing costs, and timely deliveries.

The purpose of this research is to measure objective functions such as maintenance cost, production cost, and quality cost in two machines in a sequence using a mathematical model. Once the effects are quantified, they are simultaneously optimized using an evolutionary algorithm, such as Simulated Annealing. The results of the algorithm will minimize the objective functions, such as the operation cost, the delivery time, and the product defects.

Joint consideration of production scheduling, maintenance planning, and quality control has shown promising results. A reduction of about 15% of the total operation cost has been recorded. However, the study examines only one machine. In order to reflect a real-life production structure, a multi-machine setup needs to be examined. It is hoped that through better modelling of the objective functions and jointly optimizing them, a more effective policy can be achieved. This policy can in turn act a practical guide to managers whose ultimate goal is to remain competitive.

This talk is part of the DIAL seminars series.

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