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An Efficient Jaya Algorithm for Joint Optimization of Preventive Maintenance and Quality Policy in Production Systems
Mishra A.K., Rastogi R.,
Published in Elsevier B.V.
Volume: 107
Pages: 1299 - 1304
The present paper develops an integrated approach for joint optimization of preventive maintenance (PM) planning and quality control policy in a single machine manufacturing system. Considering the economic dependency between quality and maintenance parameters, the proposed model aims to optimize the four decision variables, viz. PM interval, sample size, sample frequency and control limit coefficient to minimize the expected total integrated cost per unit time. The imperfect age-based PM model is applied which addresses the most practical issue that a unit may not always be maintained to an as-good-as-new state. Analysing the problem to be NP-hard in nature, a recently developed meta-heuristic named Jaya algorithm is applied to retrieve the near-optimum solutions. The peculiarity of Jaya as compared to conventional heuristics is that it is a parameter-less algorithm thus does not require tuning to algorithm-specific parameters thereby minimizing computational complexity to a great extent. A numerical example is presented to demonstrate the effectiveness of the integrated economic design of PM and process quality control parameters. Computational results reveal the effectiveness of the proposed approach. © 2022 The Authors. Published by Elsevier B.V.
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Published in Elsevier B.V.
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