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Fuzzy testing of operating performance index based on confidence intervals

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  • Kuen-Suan Chen

    (National Chin-Yi University of Technology
    Asia University)

Abstract

The operating performance index (OPI) was developed by Chen and Yang (J Comput Appl Math 343:737–747, 2018) from the Six Sigma process quality index. The fact that OPIs include unknown parameters means that they must be formulated using estimates based on sample data. Unfortunately, cost and effectiveness considerations in practice have led to sample size limitation and measurement uncertainty. In this study, we sought to enhance testing accuracy and overcome the uncertainties in measurement by applying confidence intervals of OPI to derive a fuzzy number and membership function for OPI. We developed a one-tailed fuzzy test method to determine whether performance reaches the required level. We also developed a two-tailed fuzzy testing method based on two OPIs to serve as a verification model for the effectiveness of improvement measures. Both fuzzy testing methods are proposed based on confidence intervals of the indices to reduce the risk of misjudgment caused by sampling errors and enhance testing accuracy.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:311:y:2022:i:1:d:10.1007_s10479-019-03242-x
    DOI: 10.1007/s10479-019-03242-x
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    References listed on IDEAS

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    1. Atar, Rami & Biswas, Anup & Kaspi, Haya, 2018. "Law of large numbers for the many-server earliest-deadline-first queue," Stochastic Processes and their Applications, Elsevier, vol. 128(7), pages 2270-2296.
    2. 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.
    3. 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.
    4. 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.
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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. Tian Chen & Ting-Hsin Hsu & Kuen-Suan Chen & Chun-Ming Yang, 2022. "A Fuzzy Improvement Testing Model of Bank APP Performance," Mathematics, MDPI, vol. 10(9), pages 1-10, April.
    3. 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.
    4. Yin-Yin Huang & Ruey-Chyn Tsaur & Nei-Chin Huang, 2022. "Sustainable Fuzzy Portfolio Selection Concerning Multi-Objective Risk Attitudes in Group Decision," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    5. Chun-Ming Yang & Tsun-Hung Huang & Kuen-Suan Chen & Chi-Han Chen & Shiyao Li, 2022. "Fuzzy Quality Evaluation and Analysis Model for Improving the Quality of Unleaded Gasoline to Reduce Air Pollution," Mathematics, MDPI, vol. 10(15), pages 1-13, August.
    6. Kuen-Suan Chen & Feng-Chia Li & Kuei-Kuei Lai & Jung-Mao Lin, 2022. "Green Outsourcer Selection Model Based on Confidence Interval of PCI for SMT Process," Sustainability, MDPI, vol. 14(24), pages 1-12, December.

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