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A process capability index for normal random variable with intuitionistic fuzzy information

Author

Listed:
  • Gholamreza Hesamian

    (Payame Noor University)

  • Mohamad Ghasem Akbari

    (University of Birjand)

Abstract

In this study, a process control criterion was extended based on intuitionistic fuzzy information in cases where the underlying population is normal with intuitionistic fuzzy mean and exact variance. The proposed process control criterion was constructed based on the arithmetic operations and a common distance measure in the space of intuitionistic fuzzy numbers. For this purpose, one of the most popular process capability indices and its corresponding estimator were extended based on intuitionistic fuzzy specific limits and intuitionistic fuzzy target when the intuitionistic fuzzy mean and/or variance are unknown. A criterion was also proposed to investigate the level of process condition. The effectiveness of the proposed method was also examined by a practical example.

Suggested Citation

  • Gholamreza Hesamian & Mohamad Ghasem Akbari, 2021. "A process capability index for normal random variable with intuitionistic fuzzy information," Operational Research, Springer, vol. 21(2), pages 951-964, June.
    • Handle: RePEc:spr:operea:v:21:y:2021:i:2:d:10.1007_s12351-019-00490-4
    DOI: 10.1007/s12351-019-00490-4
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    References listed on IDEAS

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    1. Lee, Hong Tau, 2001. "Cpk index estimation using fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 129(3), pages 683-688, March.
    2. Zhuosheng Jia & Yingjun Zhang, 2019. "Interval-Valued Intuitionistic Fuzzy Multiple Attribute Group Decision Making with Uncertain Weights," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-9, March.
    3. Jiangxia Nan & Ting Wang & Jingjing An, 2016. "Intuitionistic Fuzzy Distance Based TOPSIS Method and Application to MADM," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 5(1), pages 43-56, January.
    4. Zeinab Ramezani & Abbas Parchami & Mashaallah Mashinchi, 2011. "Fuzzy confidence regions for the Taguchi capability index," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(6), pages 977-987.
    5. A. Parchami & M. Mashinchi, 2010. "A new generation of process capability indices," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(1), pages 77-89.
    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. 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.

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