Enhancing inspection efficiency in high-quality environments using a process capability-based skip-lot sampling strategy
针对高质量制造中缺陷率极低导致传统属性检验样本量过大的问题，提出基于过程能力指数Cpk的两级跳批抽样方案，显著减少平均样本数，并通过实例验证其有效性。
This study extends the conventional skip-lot sampling (SkSP) framework by proposing a two-level skip-lot sampling plan (SkSP-2L) based on variables inspection using the process capability index Cpk. While the traditional SkSP-2L, rooted in attributes inspection, has demonstrated efficiency in reducing the average sample number (ASN), it becomes increasingly impractical in modern high-quality manufacturing environments where defect rates are extremely low. In such contexts, attributes-based methods often require prohibitively large sample sizes to ensure statistical validity. To overcome this limitation, the proposed variables-based SkSP-2L integrates the widely adopted Cpk index to facilitate more efficient and informative lot evaluation, aligned with contemporary process performance assessment practices. The study outlines the plan’s operating procedure, mathematical formulation, and sensitivity analysis. Comparative evaluations demonstrate the proposed method’s superiority over traditional SkSP-2 and single sampling plans in reducing ASN. A real-world case study further validates its practical applicability in precision-focused manufacturing settings with stringent quality requirements.