Construction of an Integrated Sampling Plan With Adaptable Backtracking and Resampling Mechanisms Based on a Process Capability Index

ABSTRACT Acceptance sampling plans represent an economical method of quality verification. One approach is the single sampling plan; however, scholars have developed more advanced sampling techniques to address its poor cost‐effectiveness, including the multiple‐dependent‐state sampling plan (MDSP) with lot disposition based on historical quality information and the repetitive group sampling plan (RGSP) with resampling. Some researchers have integrated these to design an efficient sampling scheme incorporating lot‐backtracking and resampling mechanisms: the modified RGSP (MRGSP). Studies have highlighted flaws in the MDSP and RGSP sampling mechanisms. The performance of MDSP diminishes with increased lot records, whereas the RGSP may risk infinite resampling. Although improvements have been proposed for these shortcomings, the MRGSP, integrating both mechanisms, still suffers from these drawbacks. We design an integrated sampling plan (ISP) featuring adaptable lot‐backtracking and resampling mechanisms based on the process capability index to address these deficiencies. The proposed ISP reduces the inspection sample size significantly to enhance the cost‐effectiveness of the sampling inspection compared to existing plans. Moreover, because the ISP involves numerous adjustable parameters, creating a complex optimization model, we develop a cloud‐calculation application to assist in obtaining the optimal plan design. Finally, we present a practical case to demonstrate the applicability of ISP.