Discussion on “Challenges and new methods for designing reliability experiments”

Abstract

We begin with congratulation to the authors on an insightful and interesting research on designs of reliability experiments. The authors were particularly efficient in charactering the difference between reliability experiments and classical experiments, i.e., the existence of non-normal response and censored observations. Although these characteristics complicate the analysis of reliability experiments, the authors have excellently shown that ideas from design of classical experiments could be borrowed to offer well-performed methods. As indicated in section 4 of Dr. Freeman’s article, incorporation of degradation data is useful in reliability analysis. In our discussion, we aim to amplify this point with a particular focus on degradation tests, an important class of reliability test to estimate lifetime distribution.

Keywords:

• degradation
• test planning
• allocation strategy
• blocking
• repeated measurement

Acknowledgments

We would like to thank the authors and the editors for the opportunity to discuss. This work was supported by the Natural Science Foundation of China under Grants 71771221 and 71871191.

Additional information

Funding

We would like to thank the authors and the editors for the opportunity to discuss. This work was supported by the Natural Science Foundation of China under Grants 71771221 and 71871191.

Notes on contributors

Zhi-Sheng Ye

Zhi-Sheng Ye is currently an Assistant Professor with the Department of Industrial Systems Engineering & Management, National University of Singapore. His research interests include engineering statistics and reliability engineering.

Qiuzhuang Sun

Qiuzhuang Sun received a joint B.E. in Industrial Engineering & Management, and Computer Science from Shanghai Jiao Tong University, Shanghai, China, in 2015. He is currently a Ph.D. student at the Department of Industrial Systems Engineering and Management, National University of Singapore. His research interests include maintenance optimization and degradation analysis.