Reliability Engineering

Probabilistic Models and Maintenance Methods, Second Edition

By: Joel A. Nachlas

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Hardcover | 1 December 2016 | Edition Number 2

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Without proper reliability and maintenance planning, even the most efficient and seemingly cost-effective designs can incur enormous expenses due to repeated or catastrophic failure and subsequent search for the cause. Today's engineering students face increasing pressure from employers, customers, and regulators to produce cost-efficient designs that are less prone to failure and that are safe and easy to use.

The second edition of Reliability Engineering aims to provide an understanding of reliability principles and maintenance planning to help accomplish these goals. This edition expands the treatment of several topics while maintaining an integrated introductory resource for the study of reliability evaluation and maintenance planning. The focus across all of the topics treated is the use of analytical methods to support the design of dependable and efficient equipment and the planning for the servicing of that equipment. The argument is made that probability models provide an effective vehicle for portraying and evaluating the variability that is inherent in the performance and longevity of equipment.

With a blend of mathematical rigor and readability, this book is the ideal introductory textbook for graduate students and a useful resource for practising engineers.

Industry Reviews

"The text presents material in a clear and logical progression. Concepts, covered in the early chapters, are developed through to systems level prediction techniques in the final chapters. The text is appropriate for both graduate level courses and also practitioners."
- John Andrews, University of Nottingham, United Kingdom

"Overall, the text offers a well-written, cohesive, in-depth treatment of descriptive and prescriptive concepts in reliability evaluation and maintenance planning. It should prove a valuable resource for both graduate students and practicing engineers."
- Lisa Maillart, University of Pittsburgh, USA

"The book discusses reliability engineering with a combination of statistical rigor and good readability. It covers both reliability models and analysis of failure data. The text is well organized and methodological and contains examples and exercises as well. Students will certainly find it an excellent introduction to reliability concepts and modeling approaches, and practitioners will find it a great reference source."
- Bengt Klefsjoe, Lulea University of Technology, Sweden

"Professor Nachlas' book is a great contribution to regular and advanced topics in textbooks on reliability and maintenance. It covers several areas with up-to-date material, particularly in statistical analysis and preventive and predictive maintenance."
- Dragan Banjevic, University of Toronto, Canada

"The text presents material in a clear and logical progression. Concepts, covered in the early chapters, are developed through to systems level prediction techniques in the final chapters. The text is appropriate for both graduate level courses and also practitioners."
- John Andrews, University of Nottingham, United Kingdom

"Overall, the text offers a well-written, cohesive, in-depth treatment of descriptive and prescriptive concepts in reliability evaluation and maintenance planning. It should prove a valuable resource for both graduate students and practicing engineers."
- Lisa Maillart, University of Pittsburgh, USA

"The book discusses reliability engineering with a combination of statistical rigor and good readability. It covers both reliability models and analysis of failure data. The text is well organized and methodological and contains examples and exercises as well. Students will certainly find it an excellent introduction to reliability concepts and modeling approaches, and practitioners will find it a great reference source."
- Bengt Klefsjoe, Lulea University of Technology, Sweden

"Professor Nachlas' book is a great contribution to regular and advanced topics in textbooks on reliability and maintenance. It covers several areas with up-to-date material, particularly in statistical analysis and preventive and predictive maintenance."
- Dragan Banjevic, University of Toronto, Canada

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