Reliability Engineering: Probabilistic Models and Maintenance Methods, Second Edition

Joel A. Nachlas

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December 1, 2016 by CRC Press
Textbook - 378 Pages - 148 B/W Illustrations
ISBN 9781498752473 - CAT# K27307

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Features

Offers significantly expanded treatment of statistical estimation methods for reliability data

Includes new recently published results for condition based preventive maintenance

Presents a thorough treatment of step stress testing. Also covers common cause and dependent failure models

Increased coverage of models of failure processes including gamma process and diffusion-based level crossing models

Expanded and more complete treatment of reliability growth models

Increased number of exercise problems at the end of all chapters

Summary

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.

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