Reliability: The Other Dimension of Quality

Abstract

During the past twenty years, manufacturing industries, particularly in the United States, have gone through a revolution in the use of statistical methods for product quality. Tools for process monitoring and experimental design are much more commonly used today to maintain and improve product quality. A natural extension of the revolution in product quality is to turn focus to product reliability, which is defined as “quality over time.” This has given rise to programs like Design for Six Sigma. In this paper we discuss the relationship between engineering quality and reliability and outline the role of statistics and statisticians in the field of reliability. We provide a brief introduction to the statistical tools used in engineering reliability and make some predictions for the future of statistics in engineering reliability.

Key Words:

• Demonstration test
• maximum likelihood
• reliability assurance
• reliability data
• robust design
• warranty data

Additional information

Notes on contributors

William Q. Meeker

William Q. Meeker Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. His interests are in the areas of reliability data analysis, statistical methods for quality improvement, statistical planning and inference, and statistical computing. He is a Fellow of the American Statistical Association and an elected member of the International Statistics Institute. Dr. Meeker is a former editor of Technometrics. He is the co-author of two books, five book chapters, and of numerous publications in the engineering and statistical literature.

Luis A. Escoba

Luis A. Escobar Professor in the Department of Experimental Statistics, Louisiana State University. His research and consulting interests include statistical analysis of reliability data, accelerated testing, survival analysis, linear and non-linear models. Professor Escobar is a Fellow of the American Statistical Association and an elected member of the International Statistics Institute. He is the co-author of Statistical Methods for Reliability Data (Wiley, 1998), and several other book chapters. His publications have appeared in the engineering and statistical literature.