Developing process-yield-based acceptance sampling plans for AR(1) auto-correlated process

Abstract

Acceptance sampling plans include a sampling scheme and a set of rules to determine whether an inspection lot from a supplier should be accepted or rejected. This paper aims at developing two acceptance sampling plans by variables inspection, namely a quick switching sampling (QSS) system and the modified repetitive group sampling (Modified-RGS) plan based on the process yield index Spk for the first-order auto-regressive (AR(1)) auto-correlated process. A minimization model is employed to solve the plan parameters. The performance of the proposed sampling plans is investigated and compared with the existing sampling plans through the operating characteristic (OC) curve and the average sample number (ASN) required for inspection. The simulation results confirm the advantages of the proposed plans over existing sampling plans. An example is presented to illustrate the applicability of the proposed plans.

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