Reliability Engineering

Get a firm handle on the engineering reliability process with this insightful and complete resource

Named one of the Best Industrial Management eBooks of All Time by BookAuthority
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The newly and thoroughly revised 3rd Edition of Reliability Engineering delivers a comprehensive and insightful analysis of this crucial field. Accomplished author, professor, and engineer, Elsayed. A. Elsayed includes new examples and end-of-chapter problems to illustrate concepts, new chapters on resilience and the physics of failure, revised chapters on reliability and hazard functions, and more case studies illustrating the approaches and methodologies described within.

The book combines analyses of system reliability estimation for time independent and time dependent models with the construction of the likelihood function and its use in estimating the parameters of failure time distribution. It concludes by addressing the physics of failures, mechanical reliability, and system resilience, along with an explanation of how to ensure reliability objectives by providing preventive and scheduled maintenance and warranty policies.

This new edition of Reliability Engineering covers a wide range of topics, including:

• Reliability and hazard functions, like the Weibull Model, the Exponential Model, the Gamma Model, and the Log-Logistic Model, among others
• System reliability evaluations, including parallel-series, series-parallel, and mixed parallel systems
• The concepts of time- and failure-dependent reliability within both repairable and non-repairable systems
• Parametric reliability models, including types of censoring, and the Exponential, Weibull, Lognormal, Gamma, Extreme Value, Half-Logistic, and Rayleigh Distributions

Perfect for first-year graduate students in industrial and systems engineering, Reliability Engineering, 3rd Edition also belongs on the bookshelves of practicing professionals in research laboratories and defense industries. The book offers a practical and approachable treatment of a complex area, combining the most crucial foundational knowledge with necessary and advanced topics.