Acceptance sampling plan based on an exponentially weighted moving average statistic with the yield index for autocorrelation between polynomial profiles. Issue 19 (2nd October 2018)

• Record Type: Journal Article
• Authors: Wang, Fu-Kwun; Tamirat, Yeneneh
• Is Part Of: Communications in statistics. Volume 47:Issue 19(2018)
• Page Start: 4859
• Page End: 4871
• Publication Date: 2018-10-02
• Subjects: Acceptance sampling plan -- autocorrelation between polynomial profiles -- exponentially weighted moving average -- yield index; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2018.1454960
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: Acceptance sampling plans based on process yield indices provide a proven resource for the lot-sentencing problem when the required fraction defective is very low. In this study, a new sampling plan based on the exponentially weighted moving average (EWMA) model with yield index for lot sentencing for autocorrelation between polynomial profiles is proposed. The advantage of the EWMA statistic is the accumulation of quality history from previous lots. In addition, the number of profiles required for lot sentencing is more economical than in the traditional single sampling plan. Considering the acceptable quality level (AQL) at the producer's risk and the lot tolerance percent defective (LTPD) at the consumer's risk, we proposed a new search algorithm to determine the optimal plan parameters. The plan parameters are tabulated for various combinations of the smoothing constant of the EWMA statistic, AQL, LTPD, and two risks. A comparison study and two numerical examples are provided to show the applicability of the proposed sampling plan.