Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system |
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Authors: | Abdelhakim Khatab Claver Diallo El-Houssaine Aghezzaf Uday Venkatadri |
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Affiliation: | 1. Laboratory of Industrial Engineering, Production and Maintenance (LGIPM), Lorraine University, Metz, France;2. Industrial Engineering, Dalhousie University, Halifax, Nova Scotia, Canada;3. Department of Industrial Systems Engineering and Product Design, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium;4. ISyE, Flanders Make, Belgium |
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Abstract: | This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in ‘fail mode’ whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach. |
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Keywords: | integrated production quality and maintenance condition-based maintenance degradation monitoring reliability optimization stochastic processes |
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