The application of statistical analysis to reliability, maintainability, and supportability data offers huge potential to producer and consumer alike in terms of accurate prediction of system performance measures such as availability and cost effectiveness. In addition quantitative analysis of a system is an objective means to evaluate alternative prospective designs and to measure system behavior against prescribed figures of merit.
This tutorial introduces the key concepts & techniques commonly used in the statistical analysis of reliability, maintainability, and supportability data. The rationale behind the use of both qualitative and quantitative tools to advance understanding of the underlying failure processes at work in a given system is explained, as a prelude to definition of the key concepts associated with the statistical analysis of such data. Identification & application of the appropriate analysis methods for any particular situation are discussed in terms of the mechanics of analysis itself, interpretation of the results, and common pitfalls to avoid.
Caroline Lubert graduated from the University of Exeter, UK with a BSc (1984) in Mathematics. She obtained a Ph.D. (1988) in Engineering (Exeter) for work in aeroacoustics that was conducted in association with British Petroleum plc. From 1988-1992 she was a postdoctoral research fellow in the School of Engineering at the University of Exeter, where she worked on the development of mathematical models of crossflow microfiltration systems. She was a Lecturer in the School of Mathematics and Statistics at the University of Plymouth, UK. from 1990 to1999. Since 1999 she has been a Professor of Mathematics at James Madison University in Virginia. She has published numerous technical papers, and is the JMU College of Science and Mathematics Madison Scholar for 2009. Her research interests are in combining reliability theory with engineering practice to develop mathematical models that relate to real applications, and jet noise modeling.
Clifford Lange is a Senior Consultant at Structural Integrity Assoc. Inc. He received his B.S. from Penn State in 1978, his M.S. from U.C. Berkeley in 1982 and his Ph.D. from Stanford University in 1996. In addition to serving on the management committee of the Annual Reliability and Maintainability Symposium he is an active member of the Metrics committee for the Semiconductor Equipment Manufacturing Institute. His research activities include probabilistic modeling and reliability analysis, fatigue, fracture mechanics, and creep damage failure mechanisms.
Introduction to Life Data Analysis
Session: 5A, Tuesday 8:00-12:15
Core Tutors: Caroline Lubert, Ph.D., and Clifford Lange, Ph.D.
The application of statistical analysis to reliability, maintainability, and supportability data offers huge potential to producer and consumer alike in terms of accurate prediction of system performance measures such as availability and cost effectiveness. In addition quantitative analysis of a system is an objective means to evaluate alternative prospective designs and to measure system behavior against prescribed figures of merit.
This tutorial introduces the key concepts & techniques commonly used in the statistical analysis of reliability, maintainability, and supportability data. The rationale behind the use of both qualitative and quantitative tools to advance understanding of the underlying failure processes at work in a given system is explained, as a prelude to definition of the key concepts associated with the statistical analysis of such data. Identification & application of the appropriate analysis methods for any particular situation are discussed in terms of the mechanics of analysis itself, interpretation of the results, and common pitfalls to avoid.