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Developing one-sided specification six-sigma fuzzy quality index and testing model to measure the process performance of fuzzy information

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  • Chen, Kuen-Suan
  • Wang, Ching-Hsin
  • Tan, Kim Hua
  • Chiu, Shun-Fung

Abstract

Depending on the quality characteristic, a process capability index (PCI) can be used for one-sided specifications or for bilateral specifications. A number of researchers have investigated the statistical properties of one-sided specification indices and proposed methods for applications. The later introduction of the Six Sigma approach also assisted many firms in effectively enhancing their production capacities, reducing waste, and increasing effectiveness. Chen et al. (2017a) modified the PCI for one-sided specifications and proposed the Six Sigma Quality Index (SSQI), which coincidently equals the quality level and has a one-to-one relationship with yield. However, uncertainty in quality characteristic measurements is common in practice, which can lead to judgment errors in conventional process capability assessment methods. This study therefore developed an SSQI for one-sided specifications based on the fuzzy testing method created by Buckley (2005) and developed a Six Sigma fuzzy evaluation index and testing model. In addition to having a simpler calculation procedure, the model takes the process capability and Six Sigma quality level into consideration and can process the uncertainties in the data to make it more convenient for the industry to solve engineering issues. Finally, we presented a practical example to demonstrate the applications. The model proposed in this study can provide the industry with a practical approach to assess process quality in a fuzzy environment.

Suggested Citation

  • Chen, Kuen-Suan & Wang, Ching-Hsin & Tan, Kim Hua & Chiu, Shun-Fung, 2019. "Developing one-sided specification six-sigma fuzzy quality index and testing model to measure the process performance of fuzzy information," International Journal of Production Economics, Elsevier, vol. 208(C), pages 560-565.
  • Handle: RePEc:eee:proeco:v:208:y:2019:i:c:p:560-565
    DOI: 10.1016/j.ijpe.2018.12.025
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    References listed on IDEAS

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    1. K. Chen & L. Ouyang & C. Hsu & C. Wu, 2009. "The communion bridge to Six Sigma and process capability indices," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(3), pages 463-469, May.
    2. Prasad, Sameer & Bramorski, Tom, 1998. "Robust Process Capability Indices," Omega, Elsevier, vol. 26(3), pages 425-435, June.
    3. K. Chen & H. Huang & Chiao Huang, 2007. "Control Charts for One-sided Capability Indices," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(3), pages 413-427, June.
    4. Kuen-Suan Chen & Hsi-Tien Chen & Tsang-Chuan Chang, 2017. "The construction and application of Six Sigma quality indices," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2365-2384, April.
    5. Kuen-Suan Chen & Kung-Jeng Wang & Tsang-Chuan Chang, 2017. "A novel approach to deriving the lower confidence limit of indices , , and in assessing process capability," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 4963-4981, September.
    6. Wu, Chien-Wei, 2009. "Decision-making in testing process performance with fuzzy data," European Journal of Operational Research, Elsevier, vol. 193(2), pages 499-509, March.
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    Cited by:

    1. Kuen-Suan Chen & Chun-Min Yu, 2022. "Lifetime performance evaluation and analysis model of passive component capacitor products," Annals of Operations Research, Springer, vol. 311(1), pages 51-64, April.
    2. Kuen-Suan Chen & Chun-Min Yu, 2024. "Confidence-interval-based fuzzy supplier selection model with lifetime performance index," Annals of Operations Research, Springer, vol. 340(1), pages 133-147, September.
    3. Wei Lo & Chun-Ming Yang & Kuei-Kuei Lai & Shao-Yu Li & Chi-Han Chen, 2021. "Developing a Novel Fuzzy Evaluation Model by One-Sided Specification Capability Indices," Mathematics, MDPI, vol. 9(10), pages 1-11, May.
    4. Kuen-Suan Chen, 2022. "Fuzzy testing of operating performance index based on confidence intervals," Annals of Operations Research, Springer, vol. 311(1), pages 19-33, April.
    5. Chun-Ming Yang & Chang-Hsien Hsu & Tian Chen & Shiyao Li, 2024. "Hybrid Fuzzy Method for Performance Evaluation of City Construction," Mathematics, MDPI, vol. 12(17), pages 1-13, September.
    6. Wang, Ching-Hsin & Chen, Kuen-Suan, 2020. "New process yield index of asymmetric tolerances for bootstrap method and six sigma approach," International Journal of Production Economics, Elsevier, vol. 219(C), pages 216-223.
    7. Yoon, Man Geun & Kim, Jin Ki, 2022. "Evaluation methodology for safety maturity in air navigation safety," Journal of Air Transport Management, Elsevier, vol. 98(C).
    8. Kuo-Ching Chiou, 2023. "Building Up of Fuzzy Evaluation Model of Life Performance Based on Type-II Censored Data," Mathematics, MDPI, vol. 11(17), pages 1-12, August.
    9. Tai-Shan Lee & Ching-Hsin Wang & Chun-Min Yu, 2019. "Fuzzy Evaluation Model for Enhancing E-Learning Systems," Mathematics, MDPI, vol. 7(10), pages 1-11, October.
    10. Kuen-Suan Chen & Ming-Chieh Huang & Chun-Min Yu & Hsuan-Yu Chen, 2022. "Quality-Based Supplier Selection Model for Products with Multiple Quality Characteristics," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
    11. Kuen-Suan Chen & Chun-Min Yu, 2024. "Developing a novel fuzzy testing model for capability index with asymmetric tolerances," Annals of Operations Research, Springer, vol. 340(1), pages 149-162, September.

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