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Fuzzy Evaluation Model for Lifetime Performance Using Type-I Censoring Data

Author

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  • Kuo-Ching Chiou

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

  • Tsun-Hung Huang

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan)

  • Kuen-Suan Chen

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
    Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan
    Department of Business Administration, Asia University, Taichung 413305, Taiwan)

  • Chun-Min Yu

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan)

Abstract

As global warming becomes increasingly serious, humans start to consider how to coexist with the natural environment. People become more and more aware of environmental protection and sustainable development. Therefore, in the pursuit of economic growth, it has become a consensus that enterprises should be responsible for the social and ecological environment. Regarding the manufacturing of electronic devices, as long as both component production quality and assembly quality are ensured, consumers can be provided with high-quality, safe, and efficient products. In light of this trend, enhancing product availability and reliability can reduce costs and carbon emissions resulting from repairing or replacing components, thus becoming a vital factor for corporate and environmental sustainability. Accordingly, enterprises enhance their economic benefits as well as have the effects of energy conservation and waste reduction by extending products’ service lifetime and increasing their added value. According to several studies, it takes a long time to retrieve electronic products’ lifetime data. Moreover, acquiring complete samples is often challenging. Consequently, when analyzing real cases, samples are usually collected using censoring techniques. The type-I right censoring data is suitable for industrial processes. Thus, this study utilized type-I right censoring sample data to estimate the lifetime performance index. It usually takes a large amount of time to access lifetime data for electronic products and it is often impossible to obtain complete samples since the size of the sample is usually small. Hence, to avoid misjudgment caused by sampling errors, this study followed suggestions from existing research and applied fuzzy tests built on confidence intervals to establish a fuzzy evaluation model for the lifetime performance index. This model helps relevant electronic industries not only evaluate the lifetime of their electronic components but also instantly seize opportunities for improvement.

Suggested Citation

  • Kuo-Ching Chiou & Tsun-Hung Huang & Kuen-Suan Chen & Chun-Min Yu, 2024. "Fuzzy Evaluation Model for Lifetime Performance Using Type-I Censoring Data," Mathematics, MDPI, vol. 12(13), pages 1-16, June.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:1935-:d:1419992
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    References listed on IDEAS

    as
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    3. Wen-Chuan Lee & Jong-Wuu Wu & Ching-Wen Hong & Shie-Fan Hong, 2013. "Evaluating the Lifetime Performance Index Based on the Bayesian Estimation for the Rayleigh Lifetime Products with the Upper Record Values," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-13, March.
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