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Inspection planning based on preventive maintenance condition in a serial multistage manufacturing system under uncertainty

Abstract : Part Quality Inspection Planning (PQIP) is a significant problem in multi-stage manufacturing systems. Because of an existing strong impact of Preventive Maintenance (PM) activities on the defective production rate (which is the main input of the PQIP), developing an integrated planning for the part quality inspection and PM protects system from a local optimum. This thesis presents mixed-integer linear programming models for the integrated planning problem of the part quality inspection and PM activities in a serial multi-stage manufacturing system. The models concurrently determine the right time and place for performing the above-mentioned activities while the stages are deteriorating. These two decisions are made while the models are to minimize the total cost (including the production, PM, inspection, scrap, repair, and the penalty of shipped defective items) and maximize system productivity. Notably, the system productivity is formulized as a non-linear measure, and then it is linearized by the piecewise linear approximation technique. In addition, the uncertainty about the estimation of cost components and demand is handled by a robust possibilistic approach. A numerical example and a real case study are investigated to validate and verify the proposed models. The most important result of this research is that the determination of inspection locations along a manufacturing line in different periods of time regarding the impact of preventive maintenance activities on defective production probability results in a more efficient system.
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Submitted on : Tuesday, June 23, 2020 - 10:50:20 AM
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  • HAL Id : tel-02878530, version 1


Mohammad Rezaeimalek. Inspection planning based on preventive maintenance condition in a serial multistage manufacturing system under uncertainty. Other [cs.OH]. Ecole nationale supérieure d'arts et métiers - ENSAM; University of Teheran, 2019. English. ⟨NNT : 2019ENAM0007⟩. ⟨tel-02878530⟩



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