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Stepwise inspection in Bayesian multiattribute acceptance sampling

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  • Kwei Tang
  • Robert Plante
  • Herbert Moskowitz

Abstract

Bayesian models for multiattribute acceptance sampling have been developed under the assumption that sampling inspection is carried to completion. A Bayesian multiattribute model for stepwise sampling inspection is proposed, whereby sampling inspection is terminated as soon as the disposition of the inspection lot is determined. An iterative solution procedure is developed for obtaining optimal or near‐optimal multiattribute acceptance sampling plans under stepwise sampling inspection. The effect of stepwise sampling inspection on the characteristics of an optimal sampling plan is investigated. It is shown that stepwise sampling inspection achieves a sampling plan with lower total expected cost than complete sampling inspection. In addition, it is shown that the sequence of attributes in a stepwise sampling inspection substantially affects the sampling plan and resultant expected cost. The proposed methodology is used to evaluate various heuristics which may be used to determine the sequence of attributes in a stepwise inspection procedure.

Suggested Citation

  • Kwei Tang & Robert Plante & Herbert Moskowitz, 1987. "Stepwise inspection in Bayesian multiattribute acceptance sampling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(4), pages 469-485, August.
    • Handle: RePEc:wly:navres:v:34:y:1987:i:4:p:469-485
    DOI: 10.1002/1520-6750(198708)34:43.0.CO;2-G
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    References listed on IDEAS

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    1. Herbert Moskowitz & William L. Berry, 1976. "A Bayesian Algorithm for Determining Optimal Single Sample Acceptance Plans for Product Attributes," Management Science, INFORMS, vol. 22(11), pages 1238-1250, July.
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