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Stepwise inspection in Bayesian multiattribute acceptance sampling
Author(s) -
Tang Kwei,
Plante Robert,
Moskowitz Herbert
Publication year - 1987
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/1520-6750(198708)34:4<469::aid-nav3220340403>3.0.co;2-g
Subject(s) - acceptance sampling , sampling (signal processing) , heuristics , computer science , bayesian probability , plan (archaeology) , statistics , mathematics , artificial intelligence , mathematical optimization , sample size determination , filter (signal processing) , computer vision , archaeology , history
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.