The purpose of this tutorial is to provide attendees with basic coverage of the traditional, fundamental probability models used to describe, improve, and optimize system reliability and maintainability. This coverage requires the discussion of some basic concepts from probability and distribution theory. No specific models are endorsed. Instead, emphasis is placed on identifying the key assumptions associated with each model.

Richard Cassady is a Professor in the Department of Industrial Engineering and the Director of the Freshman Engineering Program at the University of Arkansas. Prior to joining the faculty at UofA, he was on the faculty at Mississippi State University. He received his Ph.D., M.S. and B.S. all in industrial and systems engineering from Virginia Tech. His primary reliability research interests are in repairable systems modeling. This work includes the analysis and development of equipment maintenance policies including preventive maintenance, selective maintenance and cannibalization. He is a Senior Member of IIE, and a member of ASEE, INFORMS and SRE. He is also a member of the RAMS Management Committee.

In this presentation a product is followed from design inception to product retirement. The appropriate location and use of (1) Over Stress Tests, (2) Design Reviews, (3) FMEA, (4) Reliability System Analysis, (5) Accelerated Life Tests, (6) Real Time Life Tests, (7) Reliability Growth Tests, (8) Burn-In, (9) Environmental Stress Screens and (10) Statistical Process Control are discussed. Finally, field failures and the steps necessary to insure that the resulting engineering change orders yield improved reliability are covered. This paper is based primarily on the observation and experience of the author which was gained during a 40-year career in reliability and quality.

Duane L. Dietrich has been director of consulting services for ReliaSoft for the last five years. During his 45+ year career he has served as a consultant to over 60 companies and government agencies both nationally and internationally. Some of his more notable clients have been the US Army, the US Navy, IBM, Cameron Oil, JPL, John Deere, Guidant, Motorola, Raytheon, General Dynamics and Xerox. In addition, he has taught over 60 short courses for industry in the areas of Engineering Statistics, Statistical Process Control, Concepts of Reliability, Reliability Testing and Large Scale Reliability Systems Analysis.

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.

A fault tree represents the causes of a specified system failure mode in terms of the failure modes of the system components. The analysis of the fault tree can produce two types of result: qualitative and quantitative. Qualitative results specify the minimal contributions of component failures which result in system failure. Quantification provides the probability or frequency of the system failure modes.

The tutorial will explain the mathematics used to perform a fault tree analysis. A considerable focus of the tutorial will also be on the development of the fault tree model from the engineering system.

John Andrews is Professor of Systems Reliability in the Department of Aeronautical and Automotive Engineering at Loughborough University, UK. He recently transferred to this department from the Mathematical Sciences Department where he had worked since he joined Loughborough University in 1989. The prime focus of his research has been on methods for predicting system reliability in terms of the component failure probabilities and a representation of the system structure. Much of this work has concentrated on the Fault Tree technique and the use of the Binary Decision Diagrams (BDDs) as an efficient and accurate solution method. He is the author of over 100 research papers on this topic and is joint author, with Bob Moss, of a text book, Reliability and Risk Assessment, now in its second edition, published by ASME. John is a member of the Safety and Reliability Group of the Institution of Mechanical Engineers (IMechE). He is also Editor of the Journal of Risk and Reliability the new part O of the IMechE Proceedings and a member of the Editorial Boards for Reliability Engineering and System Safety and Quality and Reliability Engineering International.

Failure Modes and Effects Analysis (FMEA) is potentially one of the most beneficial and productive tasks in a well structured reliability program. It has evolved from a safety analysis, usually done after the design was complete, into a powerful design tool that can be used throughout the development process to enhance product safety and reliability. A FMEA consists of examining the modes and causes of potential item failures and determining the product response to the failure. Steps can then be taken to change the design to eliminate the failure, mitigate its effects, or develop compensating provisions if the failure should occur. FMEA can be applied to hardware, software, material, and process related causes of failure.

This tutorial focuses on how to perform a FMEA, shows how the analysis results are used, and shows how it should be integrated into the design process to maximize its effectiveness. The methodology can be usefully employed throughout the design cycle from the concept stage to production and deployment. Tools have been developed to reduce the amount of labor required for the analysis and significant progress is also being made in developing automated tools to facilitate analysis.

John B. Bowles is an Associate Professor in the Computer Science and Engineering Department at the University of South Carolina where he teaches and does research in reliable system design. Previously he was employed by NCR Corporation and Bell Laboratories where he worked on several large system development projects. He holds a BS in Engineering Science from the University of Virginia, an MS in Applied Mathematics from the University of Michigan, and a PhD in Computer Science from Rutgers University. Dr. Bowles is a Senior Member of IEEE and ASQ and an ASQ Certified Reliability Engineer. He served for four years as an Associate Editor of IEEE Transactions on Reliability and is presently editor of the RMS Partnership journal, Reliability, Maintainability, and Supportability in Systems Engineering.