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Optimizing the quality control station configuration

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  • Michal Penn
  • Tal Raviv

Abstract

We study unreliable serial production lines with known failure probabilities for each operation. Such a production line consists of a series of stations, existing machines, and optional quality control stations (QCSs). Our aim is to decide on the allocation of the QCSs within the assembly line, so as to maximize the expected profit of the system. In such a problem, the designer has to determine the QCS configuration and the production rate simultaneously. The profit maximization problem is approximated assuming exponentially distributed processing times, Poisson arrival process of jobs into the system, and the existing of holding costs. The novel feature of our model is the incorporation of holding costs that significantly complicated the problem. Our approximation approach uses a branch and bound strategy that employs our fast dynamic programming algorithm for minimizing the expected operational costs for a given production rate as a subroutine. Extensive numerical experiments are conducted to demonstrate the efficiency of the branch and bound procedure for solving large scale instances of the problem and for obtaining some qualitative insights. “Ever increasing quality is mandatory—not only for corporate profitability—but also for corporate survival” Inman, Blumenfeld, Huang, and Li (Int J Prod Res 38(9) (2000), 1953–1976) © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007

Suggested Citation

  • Michal Penn & Tal Raviv, 2007. "Optimizing the quality control station configuration," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(3), pages 301-314, April.
  • Handle: RePEc:wly:navres:v:54:y:2007:i:3:p:301-314
    DOI: 10.1002/nav.20206
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    References listed on IDEAS

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    1. Bowling, Shannon R. & Khasawneh, Mohammad T. & Kaewkuekool, Sittichai & Cho, Byung Rae, 2004. "A Markovian approach to determining optimum process target levels for a multi-stage serial production system," European Journal of Operational Research, Elsevier, vol. 159(3), pages 636-650, December.
    2. Gurnani, Haresh & Drezner, Zvi & Akella, Ram, 1996. "Capacity planning under different inspection strategies," European Journal of Operational Research, Elsevier, vol. 89(2), pages 302-312, March.
    3. Rebello, Ranjit & Agnetis, Alessandro & Mirchandani, Pitu B., 1995. "Specialized inspection problems in serial production systems," European Journal of Operational Research, Elsevier, vol. 80(2), pages 277-296, January.
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    Cited by:

    1. Ping-Chen Chang, 2019. "Reliability estimation for a stochastic production system with finite buffer storage by a simulation approach," Annals of Operations Research, Springer, vol. 277(1), pages 119-133, June.
    2. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Jula, Payman & Pirayesh, Amir & Ahmadi, Hadi, 2020. "A learning-based metaheuristic for a multi-objective agile inspection planning model under uncertainty," European Journal of Operational Research, Elsevier, vol. 285(2), pages 513-537.
    3. Anna Rotondo & Paul Young & John Geraghty, 2013. "Quality risk prediction at a non-sampling station machine in a multi-product, multi-stage, parallel processing manufacturing system subjected to sequence disorder and multiple stream effects," Annals of Operations Research, Springer, vol. 209(1), pages 255-277, October.

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