Analyzing Highly Censored Reliability Data without Exact Failure Times: An Efficient Tool for Practitioners

ABSTRACT

There are many real-life situations where exact failure times are not available or not easily available for reliability analysis. Motivated by this problem, this work is concerned with the analysis of reliability data without exact failure times. The unavailability of exact failure times has compelled us to develop a simplified version of the maximum likelihood (ML) estimation for reliability parameters and measures. The approach is applicable to single-parameter reliability models including the exponential reliability model and the Weibull reliability model with an assumed or known shape parameter value. In the latter case, it takes advantage of the fact that in many practical situations a reasonable estimate of the Weibull shape parameter is attainable by certain means. This is particularly valuable for reliability assessment of highly censored Weibull data with only a few failures, because in such situations it is highly desirable or necessary to exploit prior knowledge of the Weibull shape parameter to compensate for the limited information contained in the data in the hope of making a sound assessment. This is an application in a sense of the ideas and principles of the emerging paradigm of statistical engineering. The methods are developed by practitioners and for practitioners. We show that they offer practitioners a handy and efficient tool for reliability analysis, using hard disk drive product testing as examples.

KEYWORDS:

• hard disk drive
• highly censored
• maximum likelihood estimation
• reliability
• Weibull

ACKNOWLEDGMENTS

The authors thank the anonymous reviewers for their valuable comments and suggestions that have resulted in an improved article. Cai Wen Zhang's work was supported by the National Natural Science Foundation of China under Grant No. 71102158 and also sponsored by the Scientific Reseach Foundation for the Returned Overseas Chinese Scholars, State Education Ministry. Dongsheng Xu's work was supported in part by the Ministry of Education of P. R. China under Grant No. 09YJC630235.

Additional information

Notes on contributors

Cai Wen Zhang

Cai Wen Zhang is an associate professor of management science in the Business School, Sun Yat-sen University, Guangzhou, China. He received both an M. Eng. and a Ph.D. in industrial & systems engineering from the National University of Singapore. Prior to joining Sun Yat-sen Business School, Dr. Zhang worked for five years as a statistician for the Hitachi Global Storage Technologies (Singapore). He has published papers in international peer-reviewed journals including IIE Transactions, Reliability Engineering and System Safety, European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, Quality and Reliability Engineering International, etc. His current research interests include statistical quality control, quality management, reliability, and operations management.

Tieling Zhang

Tieling Zhang received a Ph.D. from Tokyo University of Mercantile Marine, Japan, in 2001. His research interests include reliability and maintenance engineering, health prognostics, and system optimization. He has extensive industrial and academic experience in reliability. He used to work for Hitachi Global Storage Technologies (Singapore) and Vestas Technology R&D (Singapore) as a staff engineer and specialist in reliability. He has published many research articles in peer-reviewed journals and international conference proceedings. He also holds four patents.

Dongsheng Xu

Dongsheng Xu is an associate professor in the Business School, Sun Yat-sen University, Guangzhou, China. He received his B.Sc. from Tsinghua University and Ph.D. from Hong Kong University of Science and Technology. His research interests include operations research, logistics, and applied statistics.

Min Xie

Min Xie is currently a chair professor in the Department of Systems Engineering and Engineering Management, City University of Hong Kong. He has been active in areas including quality and reliability engineering and applied statistics for over two decades. Professor Xie serves as editor or associate editor and is on the editorial board of over 15 international journals. He has served as conference chair in a number of conferences and delivered keynote speeches at many others. He has authored and coauthored seven books and over 200 journal papers.