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A cost-effective sampling strategy by variables inspection for lot disposition
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DOI：10.1007/s10479-023-05776-7.png)
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Abstract
En 中文
Acceptance sampling plans are a commonly used statistical technique in quality control and assurance applications, enabling producers and consumers to make informed decisions regarding the acceptance or rejection of product lots. In contrast to traditional lot-by-lot sampling plans, skip-lot sampling plans only inspect a fraction of submitted lots and have been shown to be an efficient sampling strategy, particularly when product lots from suppliers exhibit consistent stability and high yield. This study proposes a skip-lot sampling plan by variables inspection using an advanced process capability index that combines the benefits of yield-based and loss-based indices. A mathematical model is developed to determine the plan's parameters, with the goal of minimizing the average sample number (ASN) required for inspection while accounting for quality and risk constraints specified by both business partners. The proposed plan's operating characteristics curve and ASN curve are thoroughly examined and compared to traditional plans. Additionally, a case study is presented to demonstrate the practical application of the proposed plan. This study also highlights the benefits of the proposed plan and emphasizes the importance of optimizing the sampling strategy for lot sentencing to improve quality control and reduce inspection costs.
Keywords:
Acceptance sampling
Discriminatory power
Non-linear mathematical model
Process capability indices
Skip-lot sampling plan
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