Producing products with multiple quality characteristics is always one of the concerns for an advanced manufacturing system. To assure product quality, finite automatic inspection systems should be used. Inspection planning to allocate inspection stations should then be performed to manage the limited inspection resource. Except for finite inspection station classes, in this work, the limited number of inspection stations, of each inspection station class, is considered for solving the inspection allocation problem in a multiple quality characteristic advanced manufacturing system. Since the product variety in batch production or job shop production increases to satisfy the changing requirements of the various customers, the tolerances specified will vary from time to time. This inspection allocation problem is solved using a unit cost model in which the manufacturing capability, inspection capability, and tolerance specified are concurrently considered for a multiple quality characteristic product. The situation of unbalanced tolerance design is also considered. The inspection allocation problem can then be solved according to customer requirements. Since determining the optimal inspection allocation plan seems to be impractical, as the problem size becomes large, two decision criteria (i.e. sequence order of workstation and tolerance interval) are employed separately to develop two different heuristic solution methods in this work. The performance of each method is measured in comparison with the enumeration method that generates the optimal solution. The result shows that a feasible inspection allocation plan can be determined efficiently.
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ID="A1"Correspondance and offprint requests to: Dr Yau-Ren Shiau, Department of Industrial Engineering, Feng-Chia University, 100 Wenhwa Road, Seatwen, PO Box 25–097, Taichung 407, Taiwan
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Shiau, YR. Inspection Allocation Planning for a Multiple Quality Characteristic Advanced Manufacturing System. Int J Adv Manuf Technol 21, 494–500 (2003). https://doi.org/10.1007/s001700300058
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DOI: https://doi.org/10.1007/s001700300058