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Building Up of Fuzzy Evaluation Model of Life Performance Based on Type-II Censored Data

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  • Kuo-Ching Chiou

    (Department of Finance, Chaoyang University of Technology, Taichung 413310, Taiwan)

Abstract

The semiconductor industry is a rapidly growing sector. As collection technologies for production data continue to improve and the Internet of Things matures, production data analysis improves, thus accelerating progress towards smart manufacturing. This not only enhances the process quality, but also increases product lifetime and reliability. Under the assumption of exponential distribution, the ratio of lifetime and warranty has been proposed as a lifetime performance index for electronic products. As unknown parameters of the index, to use point estimates to assess lifetime performance may cause misjudgment due to sampling errors. In addition, cost and time limitations often lead to small sample sizes that can affect the results of the analysis. Type-II censored data are widely applied in production and manufacturing engineering. Thus, this paper proposes an unbiased and consistent estimator of lifetime performance based on type-II censored data. The 100(1 − α )% confidence interval of the proposed index is derived based on its probability density function. Overly small sample sizes not only make the length estimates of lifetime performance index intervals for electronic products too long, but they also increase sampling errors, which distort the estimation and test results. We therefore used the aforementioned interval to construct a fuzzy test model for the assessment of product lifetime and further help manufacturers to be more prudent and precise to evaluate the performance of product life cycles. A numerical example illustrates the applicability of the proposed model.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3686-:d:1226321
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    References listed on IDEAS

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    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.
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    8. 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.
    9. Kuen-Suan Chen & Chin-Chia Liu & Chi-Han Chen, 2022. "Fuzzy Evaluation of Process Quality with Process Yield Index," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
    10. 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:

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