IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i13p1935-d1419992.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/13/1935/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/13/1935/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. To-Cheng Wang & Chien-Wei Wu & Ming-Hung Shu, 2022. "A variables-type multiple-dependent-state sampling plan based on the lifetime performance index under a Weibull distribution," Annals of Operations Research, Springer, vol. 311(1), pages 381-399, April.
    3. 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.
    4. Shu-Fei Wu & Jyun-Jhe Jheng & Wei-Tsung Chang, 2023. "Sampling design for the lifetime performance index of exponential lifetime distribution under progressive type I interval censoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(8), pages 2766-2782, April.
    5. Yang, Yang & Jiang, Yan, 2023. "Buyer-supplier CSR alignment and firm performance: A contingency theory perspective," Journal of Business Research, Elsevier, vol. 154(C).
    6. Wang, Chi-Tai & Chiu, Chui-Sheng, 2014. "Competitive strategies for Taiwan's semiconductor industry in a new world economy," Technology in Society, Elsevier, vol. 36(C), pages 60-73.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kuen-Suan Chen & Tsun-Hung Huang & Jin-Shyong Lin & Chun-Min Yu & Chun-Ming Yang, 2023. "Fuzzy Evaluation Model of Machining Process Loss," Mathematics, MDPI, vol. 11(22), pages 1-13, November.
    2. 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.
    3. Song, Yanwu & Dong, Ying, 2024. "Influence of resource compensation and complete information on green sustainability of semiconductor supply chains," International Journal of Production Economics, Elsevier, vol. 271(C).
    4. Yang, Yang & Jiang, Yan, 2023. "Does suppliers’ slack influence the relationship between buyers’ environmental orientation and green innovation?," Journal of Business Research, Elsevier, vol. 157(C).
    5. Kuen-Suan Chen & Tsun-Hung Huang & Chun-Min Yu & Hui-E Lee, 2024. "Fuzzy Evaluation Model for Operational Performance of Air Cleaning Equipment," Mathematics, MDPI, vol. 12(17), pages 1-12, August.
    6. Wang Lai Wang & Marek Kryszak, 2020. "Technological Progress and Supply Base under Uncertain Market Conditions: The Case Study of the Taiwanese c-Si Solar Industry 2016–2019," Energies, MDPI, vol. 13(21), pages 1-25, November.
    7. Eman Fathi Attia & Rewayda Tobar & Heba Farid Fouad & Hamsa Hany Ezz Eldeen & Ahmed Chafai & Wafa Khémiri, 2023. "The Nonlinear Relationship between Corporate Social Responsibility and Hospitality and Tourism Corporate Financial Performance: Does Governance Matter?," Sustainability, MDPI, vol. 15(22), pages 1-32, November.
    8. Laden Mering, 2024. "Analysis of Green HRM, Green Value Strategic Improving CSR and Green Performance in Central Kalimantan HSL Palm Companies," International Review of Management and Marketing, Econjournals, vol. 14(3), pages 113-122, May.
    9. Lin, Wen-Shyong & Lee, Mengshan & Huang, Yu-Cheng & Den, Walter, 2015. "Identifying water recycling strategy using multivariate statistical analysis for high-tech industries in Taiwan," Resources, Conservation & Recycling, Elsevier, vol. 94(C), pages 35-42.
    10. Meftah Gerged, Ali & Kuzey, Cemil & Uyar, Ali & Karaman, Abdullah S., 2023. "Does investment stimulate or inhibit CSR transparency? The moderating role of CSR committee, board monitoring and CEO duality," Journal of Business Research, Elsevier, vol. 159(C).
    11. Sun, Chenhao & Xu, Hao & Zeng, Xiangjun & Wang, Wen & Jiang, Fei & Yang, Xin, 2023. "A vulnerability spatiotemporal distribution prognosis framework for integrated energy systems within intricate data scenes according to importance-fuzzy high-utility pattern identification," Applied Energy, Elsevier, vol. 344(C).
    12. Mohammad Hakkak & Amir Hooshang Nazarpoori & Mehdi Mohammadi, 2014. "Analysis and Identification of Competitive Positions of Companies Operating in Iranian Battery Industry Using Hierarchical Analysis," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 4(12), pages 741-756, December.
    13. Ming-Fu Hsu & Chingho Chang & Jhih‐Hong Zeng, 2022. "Automated text mining process for corporate risk analysis and management," Risk Management, Palgrave Macmillan, vol. 24(4), pages 386-419, December.
    14. Vlachos, Ilias & Singh, Rajesh Kumar, 2023. "Triad structure impact on the triad resources-firm performance relationship: Theory and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    15. 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.
    16. Sudhanshu Joshi & Manu Sharma, 2022. "Sustainable Performance through Digital Supply Chains in Industry 4.0 Era: Amidst the Pandemic Experience," Sustainability, MDPI, vol. 14(24), pages 1-25, December.
    17. Muhammad Aslam & Gadde Srinivasa Rao & Mohammed Albassam, 2022. "Sampling Inspection Plan to Test Daily COVID-19 Cases Using Gamma Distribution under Indeterminacy Based on Multiple Dependent Scheme," IJERPH, MDPI, vol. 19(9), pages 1-14, April.
    18. Li, Hongkuan & He, Haiyan & Shan, Jiefei & Cai, Jingjing, 2019. "Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 136-148.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:1935-:d:1419992. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.