A Multi-objective Assessment of Process Planning in a Disruptive Reconfigurable Manufacturing System: Application of Multi-heuristics

Reconfigurable Manufacturing System is a modern manufacturing topology which has been designed at its outset according to product requirements. One main issue in the field of RMS is process planning which assigns configurations to operations, however, existing literature on process planning lacks in analyzing the quality. To overcome it, this study performs a multi-objective assessment by optimizing the total cost, the quality decay index, the diversity of operations and the reconfiguration effort. The problem is NP-hard and in order to solve it, two meta-heuristics namely, non-sorting genetic algorithm and multi-objective particle swarm optimization are administered. The results of these algorithms are compared regarding their computation time and number of Pareto solutions. Furthermore, the acquired non-dominated solutions and detailed process plans are listed according to the optimal values of objective functions. Finally, a conclusion is provided.

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