One of the most useful and effective methods with an extensive application in companies with the purpose of examining the quality of the raw material in addition to final products, is acceptance sampling plans. The inspection process is assumed to be free of errors in m More
One of the most useful and effective methods with an extensive application in companies with the purpose of examining the quality of the raw material in addition to final products, is acceptance sampling plans. The inspection process is assumed to be free of errors in most of the acceptance sampling plans. However, this assumption may not be true. In this research, an optimization model for acceptance sampling plan is developed based on Bayesian inferences in the presence of inspection errors. An economical model is designed which involves two types of inspection errors and investigates the impact of these errors on the acceptance-sampling plan. Furthermore, the sensitivity analysis is carried out to analyze the behavior of optimal solution. The numerical studies indicate that increasing the inspection error leads to decrease the sample size and acceptance number.
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