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Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory

Author

Listed:
  • Chien-Chih Wang

    (Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City 243303, Taiwan)

  • Yu-Shan Chang

    (BellWether Electronic Corporation, Taoyuan City 330010, Taiwan)

Abstract

Acceptance sampling plans are divided into attributes and variables, which are used to evaluate the mechanism for determining lot quality. Traditional attribute sampling plans usually choose the Acceptable Quality Level (AQL) for each stage based on experience but need practical guidelines to follow. Previous research endeavors have predominantly centered around statistical perspectives and emphasized the reduction of sample size or sampling frequency while allocating lesser consideration to cost factors and practical applications when formulating sampling decisions. This study proposes a dynamic sampling strategy to minimize costs and estimate AQL values and sample sizes for each stage based on product quality performance to establish a more effective and flexible sampling strategy. The study verifies the scenario in an integrated circuit (IC) testing factory, considering multiple combinations of between-batch quality conditions, within-batch quality conditions, sampling method, and cost ratio, and conducts sampling inspection simulations. When quality changes, the dynamic strategy is activated to adjust AQL. Finally, based on the sampling errors and costs in the inspection results, a comparison is made with the traditional MIL-STD-105E sampling plan, confirming that the dynamic AQL sampling plan has significantly improved performance.

Suggested Citation

  • Chien-Chih Wang & Yu-Shan Chang, 2023. "Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory," Mathematics, MDPI, vol. 11(13), pages 1-16, June.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2872-:d:1180458
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    References listed on IDEAS

    as
    1. Markowski, Edward P. & Markowski, Carol A., 2002. "Improved attribute acceptance sampling plans in the presence of misclassification error," European Journal of Operational Research, Elsevier, vol. 139(3), pages 501-510, June.
    2. Mahendra Saha & Harsh Tripathi & Sanku Dey & Sudhansu S. Maiti, 2021. "Acceptance sampling inspection plan for the Lindley and power Lindley distributed quality characteristics," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1410-1419, December.
    3. Stijn Luca, 2018. "Modified chain sampling plans for lot inspection by variables and attributes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(8), pages 1447-1464, June.
    4. Yusra Tashkandy & Walid Emam & M. Masoom Ali & Haitham M. Yousof & Basma Ahmed, 2023. "Quality Control Testing with Experimental Practical Illustrations under the Modified Lindley Distribution Using Single, Double, and Multiple Acceptance Sampling Plans," Mathematics, MDPI, vol. 11(9), pages 1-28, May.
    5. K. Govindaraju & M. Bebbington, 2015. "The Consumer’s Risk and Costs in Zero-Acceptance Number Sampling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(14), pages 2933-2944, July.
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