Reliability analysis is concerned with the analysis of devices and systems whose individual components are prone to failure. This textbook presents an introduction to reliability analysis of repairable and non-repairable systems. It is based on courses given to both undergraduate and graduate students of engineering and statistics as well as in workshops for professional engineers and scientists. As aresult, the book concentrates on the methodology of the subject and on understanding theoretical results rather than on its theoretical development. An intrinsic aspect of reliability analysis is that the failure of components is best modelled using techniques drawn from probability and statistics. Professor Zacks covers all the basic concepts required from these subjects and covers the main modern reliability analysis techniques thoroughly. These include: the graphical analysis of life data, maximum likelihood estimation and bayesian likelihood estimation. Throughout the emphasis is on the practicalities of the subject with numerous examples drawn from industrial and engineering settings.

The necessity of expertise for tackling the complicated and multidisciplinary issues of safety and risk has slowly permeated into all engineering applications so that risk analysis and management has gained a relevant role, both as a tool in support of plant design and as an indispensable means for emergency planning in accidental situations. This entails the acquisition of appropriate reliability modeling and risk analysis tools to complement the basic and specific engineering knowledge for the technological area of application.Aimed at providing an organic view of the subject, this book provides an introduction to the principal concepts and issues related to the safety of modern industrial activities. It also illustrates the classical techniques for reliability analysis and risk assessment used in current practice.

BASIC Reliability Engineering Analysis describes reliability activities as they occur during an industrial development cycle. Reliability as a function of time is discussed, along with systems modeling, predicting and estimating reliability, and quality assurance. This book is comprised of seven chapters and begins with a brief introduction to the BASIC computer language used in the programs in the text. The second chapter describes the way reliability is taken into account in different parts of the development cycle, while the third chapter discusses the basic concepts of reliability as a function of time, failure rate, and some basic statistical concepts. The fourth chapter deals with the modeling of complex systems and related topics such as availability and maintainability. The fifth chapter describes the activities that can go on early in the development cycle, while the sixth chapter gives some of the techniques that can be used to analyze data generated during development or later in the cycle when equipment is in use. The final chapter offers a brief look at quality assurance and acquaints the reader with the concepts involved, using inspection by attributes to introduce the ideas. This monograph is intended for engineers or managers with a particular interest in reliability, as well as for engineering undergraduates.

This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.

A comprehensive introduction to reliability analysis. The first section provides a thorough but elementary prologue to reliability theory. The latter half comprises more advanced analytical tools including Markov processes, renewal theory, life data analysis, accelerated life testing and Bayesian reliability analysis. Features numerous worked examples. Each chapter concludes with a selection of problems plus additional material on applications.

This textbook provides the tools for a modern post-graduate introductory course on system reliability theory. It focuses on probabilistic aspects of the theory, including recent results based on signatures, stochastic orders, aging classes, copulas and distortion (or aggregation) functions. The reader requires on an introductory knowledge on probability theory and mathematics. The book serves both for graduate students in mathematics and for engineering students in various disciplines as well as students learning survival analysis, network reliability or simple game theory. Included also are brief introductions to the basic aspects of lifetime modelling, stochastic comparisons, aging classes, mixtures and copula theory. The book develops this knowledge with worked examples and supplies code for the program R so that students can explore its lessons and techniques.

Many books on reliability focus on either modeling or statistical analysis and require an extensive background in probability and statistics. Continuing its tradition of excellence as an introductory text for those with limited formal education in the subject, this classroom-tested book introduces the necessary concepts in probability and statistics within the context of their application to reliability. The Third Edition adds brief discussions of the Anderson-Darling test, the Cox proportionate hazards model, the Accelerated Failure Time model, and Monte Carlo simulation. Over 80 new end-of-chapter exercises have been added, as well as solutions to all odd-numbered exercises. Moreover, Excel workbooks, available for download, save students from performing numerous tedious calculations and allow them to focus on reliability concepts. Ebeling has created an exceptional text that enables readers to learn how to analyze failure, repair data, and derive appropriate models for reliability and maintainability as well as apply those models to all levels of design.