Dual-response optimization for lifetime improvement experimental designs. (August 2021)

• Record Type: Journal Article
• Authors: Wang, Guodong; Shao, Mengying; Cui, Qingan; Lv, Shanshan; He, Zhen; Vining, Geoff
• Is Part Of: Computers & industrial engineering. Volume 158(2021)
• Publication Date: 2021-08
• Subjects: Dual-response optimization -- Design of experiments -- Reliability improvement -- Weibull distribution -- Warranty period; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107437
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We propose a dual response model and identify factors by a bootstrap method. A reliability-centered optimization criterion considering warranty period is provided. Reducing the variance and improving the percentile lifetime is not contradictory. The optimal solution is a piecewise function within the warranty period. Abstract: Manufacturing process parameters often affect product reliability significantly. Practitioners need to improve product lifetime and reduce its variance simultaneously by optimizing process parameters. However, an important feature of lifetime distributions is that the variance increases as the mean increases. Practitioners should make a trade-off between them. In this article, we present a dual-response optimization approach to get optimal trade-off of percentile lifetime and lifetime variance. A new criterion is introduced to maximize the product reliability in the warranty period. We illustrate the proposed method via a real example and a simulated example. The optimization results show that the optimal solution is not a constant for different warranty periods. Practitioners should select different important factor levels for different scenarios. Furthermore, we compare the proposed method with other methods. The proposed method performs better than other methods significantly. Additionally, we present some discussions about the determination of significant factor levels.