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The construction and application of Six Sigma quality indices

Author

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  • Kuen-Suan Chen
  • Hsi-Tien Chen
  • Tsang-Chuan Chang

Abstract

Process quality is the primary factor in facilitating product sales. In accordance with the concept of Six Sigma, numerous studies have employed process capability indices for the determination of process quality levels. Unfortunately, existing indices present only a range of quality levels rather than a specific quality level value. This paper aims to propose Six Sigma quality indices for the assessment of quality levels associated with unilateral as well as bilateral specifications. To ensure the reliability in process assessment, we employ the lower confidence limit of the indices to serve as a standard and develop a process quality analysis chart for the simultaneous evaluation of larger-the-better, smaller-the-better and nominal-the-best quality characteristics with the aim of identifying the causes of sub-standard quality. The resulting chart also provides a valuable reference by which to guide efforts aimed at improvement. Finally, we present three cases and numerical experiments to demonstrate the practical applicability of the proposed method.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:8:p:2365-2384
    DOI: 10.1080/00207543.2016.1246763
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    References listed on IDEAS

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    1. Chang, Y.C. & Wu, Chien-Wei, 2008. "Assessing process capability based on the lower confidence bound of Cpk for asymmetric tolerances," European Journal of Operational Research, Elsevier, vol. 190(1), pages 205-227, October.
    2. Wu, Chien-Wei & Pearn, W.L. & Kotz, Samuel, 2009. "An overview of theory and practice on process capability indices for quality assurance," International Journal of Production Economics, Elsevier, vol. 117(2), pages 338-359, February.
    3. Chen, K.S. & Chen, T.W., 2008. "Multi-process capability plot and fuzzy inference evaluation," International Journal of Production Economics, Elsevier, vol. 111(1), pages 70-79, January.
    4. Pearn, W.L. & Wu, Chien-Wei, 2006. "Production quality and yield assurance for processes with multiple independent characteristics," European Journal of Operational Research, Elsevier, vol. 173(2), pages 637-647, September.
    5. Wu, Chien-Wei, 2012. "An efficient inspection scheme for variables based on Taguchi capability index," European Journal of Operational Research, Elsevier, vol. 223(1), pages 116-122.
    6. Malin Albing & Kerstin Vännman, 2011. "Elliptical safety region plots for C pk," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(6), pages 1169-1187, April.
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    Cited by:

    1. Kuen-Suan Chen & Tsun-Hung Huang & Ruey-Chyn Tsaur & Wen-Yang Kao, 2022. "Fuzzy Evaluation Models for Accuracy and Precision Indices," Mathematics, MDPI, vol. 10(21), pages 1-12, October.
    2. 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.
    3. Kuen-Suan Chen & Tsun-Hung Huang, 2021. "A Fuzzy Evaluation Model Aimed at Smaller-the-Better-Type Quality Characteristics," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    4. Chun-Min Yu & Win-Jet Luo & Ting-Hsin Hsu & Kuei-Kuei Lai, 2020. "Two-Tailed Fuzzy Hypothesis Testing for Unilateral Specification Process Quality Index," Mathematics, MDPI, vol. 8(12), pages 1-18, November.
    5. 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.
    6. 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.
    7. 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.
    8. Mingyuan Li & Kuen-Suan Chen & Chun-Min Yu & Chun-Ming Yang, 2021. "A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index," Mathematics, MDPI, vol. 9(3), pages 1-12, January.
    9. Chun-Chieh Tseng & Kuo-Ching Chiou & Kuen-Suan Chen, 2022. "Estimation of the Six Sigma Quality Index," Mathematics, MDPI, vol. 10(19), pages 1-13, September.
    10. Kuen-Suan Chen & Tsun-Hung Huang & Kuo-Ching Chiou & Wen-Yang Kao, 2024. "Fuzzy Evaluation Model for Products with Multifunctional Quality Characteristics: Case Study on Eco-Friendly Yarn," Mathematics, MDPI, vol. 12(10), pages 1-11, May.
    11. Chen, Kuen-Suan & Wang, Ching-Hsin & Tan, Kim-Hua, 2019. "Developing a fuzzy green supplier selection model using six sigma quality indices," International Journal of Production Economics, Elsevier, vol. 212(C), pages 1-7.
    12. 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.
    13. 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.
    14. Kuen-Suan Chen & Tsang-Chuan Chang & Chien-Che Huang, 2020. "Supplier Selection by Fuzzy Assessment and Testing for Process Quality under Consideration with Data Imprecision," Mathematics, MDPI, vol. 8(9), pages 1-14, August.

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