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Process parameter optimization for lifetime improvement experiments considering warranty and customer satisfaction

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  • Wang, Guodong
  • Shao, Mengying
  • Lv, Shanshan
  • Kong, Xiangfen
  • He, Zhen
  • Vining, Geoff

Abstract

Many process parameters may affect product reliability significantly. Manufacturers need to identify the key processes and optimize their parameter levels. Traditional methods only improve product lifetime through maximizing the location parameter. They ignore the robustness of the product. In this article, we improve product lifetime and reduce variance simultaneously by changing the levels of experimental factors. Considering warranty and customer satisfaction, we introduce a new loss function, and get the average loss cost of manufacturer and customer. We obtain the optimal levels of experimental factors through minimizing the total loss cost. We illustrate the proposed method using a real industrial experiment. The results show that the optimal solution is changed with warranty period and design lifetime. Furthermore, we explain the changes of experimental factors, and discuss some related issues in actual application scenarios.

Suggested Citation

  • Wang, Guodong & Shao, Mengying & Lv, Shanshan & Kong, Xiangfen & He, Zhen & Vining, Geoff, 2022. "Process parameter optimization for lifetime improvement experiments considering warranty and customer satisfaction," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:reensy:v:221:y:2022:i:c:s0951832022000473
    DOI: 10.1016/j.ress.2022.108369
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    References listed on IDEAS

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    1. Besseris, George J., 2010. "A methodology for product reliability enhancement via saturated–unreplicated fractional factorial designs," Reliability Engineering and System Safety, Elsevier, vol. 95(7), pages 742-749.
    2. Wang, Xiaolin & Zhao, Xiujie & Liu, Bin, 2020. "Design and pricing of extended warranty menus based on the multinomial logit choice model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 237-250.
    3. Zhuang, Xiaotian & Pan, Rong & Du, Xiaoping, 2015. "Enhancing product robustness in reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 145-153.
    4. Besseris, George J., 2015. "Concurrent multiresponse non-linear screening: Robust profiling of webpage performance," European Journal of Operational Research, Elsevier, vol. 241(1), pages 161-176.
    5. Wang, Yukun & Liu, Yiliu & Liu, Zixian & Li, Xiaopeng, 2017. "On reliability improvement program for second-hand products sold with a two-dimensional warranty," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 452-463.
    6. Jianjun Wang & Yizhong Ma & Fugee Tsung & Gang Chang & Yiliu Tu, 2019. "Economic parameter design for ultra-fast laser micro-drilling process," International Journal of Production Research, Taylor & Francis Journals, vol. 57(20), pages 6292-6314, October.
    7. Kong, Xuefeng & Yang, Jun & Hao, Songhua, 2021. "Reliability modeling-based tolerance design and process parameter analysis considering performance degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    8. Freiesleben, Johannes, 2008. "A proposal for an economic quality loss function," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1012-1024, June.
    9. Wang, Guodong & He, Zhen & Xue, Li & Cui, Qingan & Lv, Shanshan & Zhou, Panpan, 2017. "Bootstrap analysis of designed experiments for reliability improvement with a non-constant scale parameter," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 114-121.
    10. Fan Jiang & Matthias Hwai Yong Tan & Kwok-Leung Tsui, 2021. "Multiple-target robust design with multiple functional outputs," IISE Transactions, Taylor & Francis Journals, vol. 53(9), pages 1052-1066, June.
    11. Besseris, George J., 2012. "Profiling effects in industrial data mining by non-parametric DOE methods: An application on screening checkweighing systems in packaging operations," European Journal of Operational Research, Elsevier, vol. 220(1), pages 147-161.
    12. Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    13. Wallace R. Blischke & M. Rezaul Karim & D. N. Prabhakar Murthy, 2011. "Warranty Data Collection and Analysis," Springer Series in Reliability Engineering, Springer, number 978-0-85729-647-4, September.
    14. Ghaderi, A. & Hassani, H. & Khodaygan, S., 2021. "A Bayesian-reliability based multi-objective optimization for tolerance design of mechanical assemblies," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
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