Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/13/2872 |
| _version_ | 1827734848607879168 |
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| author | Chien-Chih Wang Yu-Shan Chang |
| author_facet | Chien-Chih Wang Yu-Shan Chang |
| author_sort | Chien-Chih Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T01:35:12Z |
| format | Article |
| id | doaj.art-65e79b26ae424f8f8e84a219a71403be |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T01:35:12Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-65e79b26ae424f8f8e84a219a71403be2023-11-18T17:02:39ZengMDPI AGMathematics2227-73902023-06-011113287210.3390/math11132872Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test FactoryChien-Chih Wang0Yu-Shan Chang1Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City 243303, TaiwanBellWether Electronic Corporation, Taoyuan City 330010, TaiwanAcceptance 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.https://www.mdpi.com/2227-7390/11/13/2872dynamic samplingsampling errorquality costIC test factorycase simulation |
| spellingShingle | Chien-Chih Wang Yu-Shan Chang Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory Mathematics dynamic sampling sampling error quality cost IC test factory case simulation |
| title | Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory |
| title_full | Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory |
| title_fullStr | Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory |
| title_full_unstemmed | Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory |
| title_short | Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory |
| title_sort | dynamic acceptance sampling strategy based on product quality performance using examples from ic test factory |
| topic | dynamic sampling sampling error quality cost IC test factory case simulation |
| url | https://www.mdpi.com/2227-7390/11/13/2872 |
| work_keys_str_mv | AT chienchihwang dynamicacceptancesamplingstrategybasedonproductqualityperformanceusingexamplesfromictestfactory AT yushanchang dynamicacceptancesamplingstrategybasedonproductqualityperformanceusingexamplesfromictestfactory |