This approach minimizes average sample number in life testing for products, highlighting efficiency in managing sampling plans.
This article addresses the high time and cost associated with life testing by proposing a repetitive acceptance sampling plan for time-truncated life tests, specifically for the Exponentiated Frechet Distribution (EFD) with known shape parameters. The objective is to minimize the average sample number (ASN) while ensuring that the lot acceptance probabilities meet predefined quality levels. The plan characteristics, such as sample size and acceptance number, are determined based on the test’s median lifetime as a critical quality criterion. The proposed methodology is compared with the traditional single sampling plan, demonstrating its efficiency in reducing the required sample size. Additionally, a real-life data are used to illustrate the application of the method, providing practical insights. Tables are presented for various values of the shape parameters to facilitate implementation. The study contributes a novel approach to improving efficiency in life testing while maintaining reliability. The results shows that the proposed repetitive acceptance sampling plan reduces sample sizes. This consistent reduction highlights the superiority of the proposed method in terms of cost and efficiency.
No takes yet. Share an insight, caveat, or question.
Jilani et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: