Simultaneous optimization of quality and reliability characteristics through designed experiment

ABSTRACT

Many practical situations have both a quality characteristic and a reliability characteristic with the goal to find an appropriate compromise for the optimum conditions. Standard analyses of quality and reliability characteristics in designed experiments usually assume a completely randomized design. However, many experiments involve restrictions on randomization, e.g., subsampling, blocking, split-plot.

This article considers an experiment involving both a quality characteristic and a reliability characteristic (lifetime) within a subsampling protocol. The particular experiment uses Type I censoring for the lifetime. Previous work on analyzing reliability data within a subsampling protocol assumed Type II censoring. This article extends such an analysis for Type I censoring. The method then uses a desirability function approach combined with the Pareto front to obtain a trade-off between the quality and reliability characteristics. A case study illustrates the methodology.

KEYWORDS:

• designed experiments
• optimization
• quality characteristic
• reliability characteristic
• subsampling

About the authors

Shanshan Lv is a Ph.D. student in the College of Management and Economics at Tianjin University, China. She is also a joint Ph.D. student in the Department of Statistics at Virginia Tech. She received her B.S. degree in 2012 from Zhengzhou University. Her research interests include design of experiments, reliability analysis, and improvement, and multi-response optimization.

Zhen He is a professor of the College of Management and Economics at Tianjin University, China. He received his B.S., M.S., and Ph.D. degrees from Tianjin University, China, 1988, 1991, and 2000, respectively. He is an academician of International Academy for Quality (IAQ). His current research interests include reliability analysis, statistical process controls, design of experiments, response surface methodology, and six sigma.

Geoff Vining received his Ph.D. from Virginia Tech., Blacksburg. He is a Professor at Statistics Department at Virginia Tech. He also served on the faculty of the Statistics Department at the University of Florida, Gainesville, as a practicing engineer with the FaberCastell Corporation and as an industrial consultant. He received 2011 William G. Hunter Award by the American Society for Quality Statistics Division for excellence in statistics as a communicator, a consultant, an educator, an innovator, an integrator of statistics with other disciplines, and an implementer who obtains meaningful results. In 2010, Dr. Vining received the Shewhart Medal, the ASQ career award for outstanding technical leadership in the field of modern quality control. He has been Editor-in-Chief for Quality Engineering (2009–2010) and Editor for Journal of Quality Technology (1998–2000).

Funding

This study was supported by the National Natural Science Foundation of China Grants (NSFC: 71225006, 71532008, 71402118, 71661147003, and 71571168).