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An optimal plan of zero-defect single-sampling by attributes for incoming inspections in assembly lines

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  • Qin, Ruwen
  • Cudney, Elizabeth A.
  • Hamzic, Zlatan

Abstract

This paper proposes a nonlinear integer program for determining an optimal plan of zero-defect, single-sampling by attributes for incoming inspections in assembly lines. Individual parts coming to an assembly line differ in the non-conforming (NC) risk, NC severity, lot size, and inspection cost-effectiveness. The proposed optimization model is able to determine the inspection sample size for each of the parts in a resource constrained condition where a product’s NC risk is not a linear combination of NC risks of the individual parts. This paper develops a three-step solution procedure that effectively reduces the solution time for larger size problems commonly seen in assembly lines. The proposed optimization model provides insightful implications for quality management. For example, it reveals the principle of sample size decisions for heterogeneous, dependent parts waiting for incoming inspections; as well as provides a tool for quantifying the expected return from investing additional inspection resources. The optimization model builds a foundation for extensions to advanced inspection sampling plans.

Suggested Citation

  • Qin, Ruwen & Cudney, Elizabeth A. & Hamzic, Zlatan, 2015. "An optimal plan of zero-defect single-sampling by attributes for incoming inspections in assembly lines," European Journal of Operational Research, Elsevier, vol. 246(3), pages 907-915.
  • Handle: RePEc:eee:ejores:v:246:y:2015:i:3:p:907-915
    DOI: 10.1016/j.ejor.2015.05.054
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    1. Omprakash K. Gupta & A. Ravindran, 1985. "Branch and Bound Experiments in Convex Nonlinear Integer Programming," Management Science, INFORMS, vol. 31(12), pages 1533-1546, December.
    2. Markowski, Edward P. & Markowski, Carol A., 2002. "Improved attribute acceptance sampling plans in the presence of misclassification error," European Journal of Operational Research, Elsevier, vol. 139(3), pages 501-510, June.
    3. Kwei Tang & Robert Plante & Herbert Moskowitz, 1986. "Multiattribute Bayesian Acceptance Sampling Plans Under Nondestructive Inspection," Management Science, INFORMS, vol. 32(6), pages 739-750, June.
    4. Sedat Sami Ercan & M. Zia Hassan & Ajva Taulananda, 1974. "Cost Minimizing Single Sampling Plans with AIQL and AOQL Constraints," Management Science, INFORMS, vol. 20(7), pages 1112-1121, March.
    5. Kwei Tang & Jen Tang, 1989. "Design of Product Specifications for Multi-Characteristic Inspection," Management Science, INFORMS, vol. 35(6), pages 743-756, June.
    6. Balamurali, S. & Jun, Chi-Hyuck, 2007. "Multiple dependent state sampling plans for lot acceptance based on measurement data," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1221-1230, August.
    7. Ben-Daya, M. & Noman, S.M., 2008. "Integrated inventory and inspection policies for stochastic demand," European Journal of Operational Research, Elsevier, vol. 185(1), pages 159-169, February.
    8. Hsieh, Chung-Chi & Liu, Yu-Te, 2010. "Quality investment and inspection policy in a supplier-manufacturer supply chain," European Journal of Operational Research, Elsevier, vol. 202(3), pages 717-729, May.
    9. Hugo C. Hamaker, 1958. "Some Basic Principles of Sampling Inspection by Attributes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 7(3), pages 149-159, November.
    10. Shin, Sangmun & Kongsuwon, Pauline & Cho, Byung Rae, 2010. "Development of the parametric tolerance modeling and optimization schemes and cost-effective solutions," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1728-1741, December.
    11. Pearn, W.L. & Wu, Chien-Wei, 2007. "An effective decision making method for product acceptance," Omega, Elsevier, vol. 35(1), pages 12-21, February.
    12. I. D. Hill, 1960. "The Economic Incentive Provided by Sampling Inspection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 9(2), pages 69-81, June.
    13. Fernández, Arturo J. & Pérez-González, Carlos J. & Aslam, Muhammad & Jun, Chi-Hyuck, 2011. "Design of progressively censored group sampling plans for Weibull distributions: An optimization problem," European Journal of Operational Research, Elsevier, vol. 211(3), pages 525-532, June.
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    Cited by:

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    2. Pérez-González, Carlos J. & Fernández, Arturo J. & Kohansal, Akram, 2020. "Efficient truncated repetitive lot inspection using Poisson defect counts and prior information," European Journal of Operational Research, Elsevier, vol. 287(3), pages 964-974.
    3. Fernández, Arturo J., 2017. "Economic lot sampling inspection from defect counts with minimum conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 258(2), pages 573-580.

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