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Optimal acceptance sampling policy considering Bayesian risks

Adibfar, S ; Sharif University of Technology | 2017

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  1. Type of Document: Article
  2. DOI: 10.1080/03610926.2015.1099670
  3. Publisher: Taylor and Francis Inc , 2017
  4. Abstract:
  5. In this paper, we propose a sampling policy considering Bayesian risks. Various definitions of producer's risk and consumer's risk have been made. Bayesian risks for both producer and consumer are proven to give better information to decision-makers than classical definitions of the risks. So considering the Bayesian risk constraints, we seek to find optimal acceptance sampling policy by minimizing total cost, including the cost of rejecting the batch, the cost of inspection, and the cost of defective items detected during the operation. Proper distributions to construct the objective function of the model are specified. In order to demonstrate the application of the proposed model, we illustrate a numerical example. Furthermore, the results of the sensitivity analysis show that lot size, the cost of inspection, and the cost of one defective item are key factors in sampling policies. The acceptable quality level, the lot tolerance proportion defective, and Bayesian risks also affect the sampling policy, but variations of acceptable quality level and producer Bayesian risks, for values more than a specified value, cause no changes in sampling policy. © 2017 Taylor & Francis Group, LLC
  6. Keywords:
  7. Acceptance sampling ; Bayesian consumer's risk ; Bayesian producer's risk ; Costs ; Decision making ; Quality control ; Sensitivity analysis ; Acceptable quality levels ; Bayesian risks ; Consumer's risks ; Decision makers ; Defective items ; Objective functions ; Producer's risks ; Cost benefit analysis
  8. Source: Communications in Statistics - Theory and Methods ; Volume 46, Issue 11 , 2017 , Pages 5228-5237 ; 03610926 (ISSN)
  9. URL: https://www.tandfonline.com/doi/abs/10.1080/03610926.2015.1099670?journalCode=lsta20