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Relaibility and Risk Analysis Second Edition
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Katrina Groth |
2023 |
Reliability and Risk Analysis, Second Edition, emphasizes an introduction and explanation of the practical methods used in reliability and risk studies, with a discussion of their uses and limitations. It offers basic and advanced methods in reliability analysis that are commonly used in daily practice and provides methods that address unique topics such as dependent failure analysis, importance analysis, and analysis of repairable systems. The book goes on to present a comprehensive overview of modern probabilistic life assessment methods such as Bayesian estimation, system reliability analysis, and human reliability. End-of-chapter problems and a solutions manual are available to support any course adoptions. This book is refined, simple, and focuses on fundamentals. The audience is the beginner with no background in reliability engineering and rudimentary knowledge of probability and statistics. It can be used by new practitioners, undergraduates, and first-year graduate students. |
Books
Return to Publications2020-2025
2010-2019
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Mehdi Amiri Christopher Jackson |
2019 | The book presents highly technical approaches to the probabilistic physics of failure analysis and applications to accelerated life and degradation testing to reliability prediction and assessment. Beside reviewing a select set of important failure mechanisms, the book covers basic and advanced methods of performing accelerated life test and accelerated degradation tests and analyzing the test data. The book includes a large number of very useful examples to help readers understand complicated methods described. Finally, MATLAB, R and OpenBUGS computer scripts are provided and discussed to support complex computational probabilistic analyses introduced. |
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Probability Distributions Used in Reliability Engineering
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Andrew O'Connor |
2019 | This book discusses the probability distributions used in reliability engineering and risk analysis. For each distribution, the book provides graphical visualization and related formulas, along with the corresponding reliability functions and other related formulas. Common statistics such as moments and confidence interval formulas are presented, including the likelihood functions. For the most important distributions, the book provides derivation of the maximum likelihood estimates. Bayesian estimations using non-informative and conjugate priors are provided, followed by a discussion on the distribution characteristics and applications to reliability engineering. The book includes numerical examples for each distribution, demonstrating applications of the distribution function in the context of reliability engineering and risk analysis problems. Each section concludes with online resources and hardcopy references for further information, followed by the relationship of each distribution to other distributions. |
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Probabilistic Physics of Failure Approach to Reliability: Modeling, Accelerated Testing, Prognosis and Reliability Assessment |
Christopher S. Jackson Mehdi Amiri |
2017 | This book presents highly technical approaches to the probabilistic physics of failure analysis and applications to accelerated life and degradation testing to reliability prediction and assessment. Beside reviewing a select set of important failure mechanisms, the book covers basic and advanced methods of performing accelerated life test and accelerated degradation tests and analyzing the test data. The book includes a large number of very useful examples to help readers understand complicated methods described. Finally, MATLAB, R and OpenBUGS computer scripts are provided and discussed to support complex computational probabilistic analyses introduced. |
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Reliability Engineering and Risk Analysis: A Practical Guide, 3rd ed. |
Mark P. Kaminskiy |
2016 |
This undergraduate and graduate textbook provides a practical and comprehensive overview of reliability and risk analysis techniques. Written for engineering students and practicing engineers, the book is multi-disciplinary in scope. The new edition has new topics in classical confidence interval estimation; Bayesian uncertainty analysis; models for physics-of-failure approach to life estimation; extended discussions on the generalized renewal process and optimal maintenance; and further modifications, updates, and discussions. The book includes examples to clarify technical subjects and many end of chapter exercises. PowerPoint slides and a Solutions Manual are also available. |
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Engineering Decision Making and Risk Management | 2015 |
Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different qualitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. |
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Complementary Modeling in Energy Markets | 2013 |
This addition to the ISOR series introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques. In a nutshell, complementarity models generalize: a. optimization problems via their Karush-Kuhn-Tucker conditions b. on-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions) c. economic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria) d. problems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES). As such, complementarity models are a very general and flexible modeling format. A natural question is why concentrate on energy markets for this complementarity approach? As it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems. The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold. Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning. Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers. |
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Probability, Statistics and Reliability for Engineers and Scientists |
Richard McCuen |
2011 | The third edition of this bestselling text presents probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. This provides a measure of continuity and shows the broad use of simulation as a computational tool to inform decision making processes. This edition also features expanded discussions of the analysis of variance, including single- and two-factor analyses, and a thorough treatment of Monte Carlo simulation. |
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Novel and Faster Ways for Solving Semi-Markov Processes: Mathematical and Numerical Issues |
Marcio Jose das Chagas Moura |
2010 |
Semi-Markov processes (SMP) are powerful stochastic tools for modeling reliability measures over time. This work precisely aims at proposing more efficient mathematical and numerical treatments for SMP in continuous time. The first approach (called 2N-) is based on transition frequency densities and general quadrature methods. The other proposed method (in short Lap-) applies Laplace transforms that are inverted by a Gaussian quadrature method known as Gauss Legendre to obtain the state probabilities in time domain. Mathematical formulation of these approaches as well as descriptions of their numerical treatment are developed and provided with details. The effectiveness of the novel 2N- and Lap- developments is validated by using examples in the context of oil industries. It is shown that the 2N- and Lap- approaches are significantly less time-consuming and have comparable accuracy to Monte Carlo simulation based solution. |
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Support Vector Machines and Particle Swarm Optimization: Applications to Reliability Prediction |
Isis Didier Lins Marcio Jose das Chagas Moura |
2010 | Reliability is a critical indicator of organizations' performance in face of market competition, since it contributes to production regularity. Its prediction is of great interest as it may anticipate trends of system failures and thus enable maintenance actions. The consideration of all aspects that influence system reliability may render its modeling very complex and learning methods such as Support Vector Machines (SVMs) emerge as alternative prediction tools: previous knowledge about the function or process that maps input variables into output is not required. However, SVM performance is affected by parameters from the related learning problem. Suitable values for them are chosen by means of Particle Swarm Optimization (PSO), a probabilistic approach based on the behavior of organisms that move in groups. Thus, a PSO+SVM methodology is proposed to handle reliability prediction problems. It is used to solve application examples based on time series data and also involving data collected from oil production wells. The results indicate that PSO+SVM is able to provide competitive or even more accurate reliability predictions when compared, for example, to Neural Networks (NNs). |
2000-2009
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Photonic Materials, Devices and Reliability | Aris Christou | 2006 | This publication presents photonics in the context of reliability. Design concepts are presented to promote material combinations that are robust and reliable. All wearout mechanisms must be understood, as well as their effect on performance. Metalizations and their degradation mechanisms must also be understood. This book highlights their contribution to overall photonic material and device reliability. |
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Reliability of High Temperature Electronics | Aris Christou | 2006 | Standard electronic devices are based on military-type semiconductors which are rated for 125°C. Without cooling, engine-located electronics in many applications can face operating temperatures between -55°C and +200°C. Thus, the development of appropriate 200°C and higher semiconductor devices will make it necessary to utilize air or liquid as the cooling medium. This book provides a working knowledge of high temperature devices/packaging, addressing the reliability and packaging concerns for designing at elevated temperatures. |
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Reliability of Analogue Microwave Integrated Circuits |
Willie M. Webb |
2006 | Material scientists, device technologists, and microwave designers must focus on the reliability concerns of the products which are being developed from compound semiconductor structures. The book focuses on a physics of failure approach to the understanding of MMIC reliability, covering basic failure modes for each of the device building blocks, up to packaged MMIC modules. This book will allow the GaAs technologist, designer and graduate student to become familiar with the issues related to product reliability and to develop the reliability prediction tools which ensure that reliability and performance margins are designed into each product. |
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Risk Analysis in Engineering: Probabilistic Techniques, Tools and Trends | Mohammad Modarres | 2006 | This book presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the part of the student and provides the necessary mathematical and engineering foundations. The text relies heavily on, but is not limited to, examples from the nuclear industry, because that is where PRA techniques were first developed. Since PRA provides a best-estimate approach, the author pays special attention to explaining uncertainty characterization. |
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Uncertainty Modeling and Analysis in Engineering and the Sciences |
George Klir |
2006 | Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge and ignorance, how to model and analyze uncertainty, and how to select appropriate analytical tools for particular problems. This volume covers primary components of ignorance and their impact on practice and decision making. It provides an overview of the current state of uncertainty modeling and analysis, and reviews emerging theories while emphasizing practical applications in science and engineering. |
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Statistical Distribution Functions and Tables Used in Reliability Engineering |
Willie Webb Carol Smidts |
2004 | This book presents a concise statement of leading facts relating to 61 univariate distribution functions, some of which have application in reliability engineering modeling. Included are figures so that shapes and other general properties may be readily understood. These distributions provide the building blocks for reliability models and are typically defined in terms of parameters. |
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Risk Analysis in Engineering and Economics | Bilal Ayyub | 2003 |
More than any other book available, Risk Analysis in Engineering and Economics introduces the fundamental concepts, techniques, and applications of the subject in a style tailored to meet the needs of students and practitioners of engineering, science, economics, and finance. Drawing on his extensive experience in uncertainty and risk modeling and analysis, the author leads readers from the fundamental concepts through the theory, applications, and data requirements, sources, and collection. He emphasizes the practical use of the methods presented and carefully examines the limitations, advantages, and disadvantages of each. Case studies that incorporate the techniques discusses offer a practical perspective that helps readers clearly identify and solve problems encountered in practice. |
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Applied Reliability Engineering (Vol. II) |
Willie Webb |
2002 |
Volume II of the book provides a “systems view” of reliability engineering covering in chapter six the standard techniques for system reliability analysis and simulation. Chapter seven addresses techniques used in designing for reliability and maintainability. Chapter eight introduces renewal theory, condition-based maintenance and other aspects of maintainability analysis. Chapter nine provides a thorough coverage of the various aspects of development and acceptance testing as well as accelerated testing. Chapter ten then describes the design and conduct of reliability management programs. |
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Applied Reliability Engineering (Vol. I) |
Willie Webb |
2002 |
This book is organized to provide an introduction to reliability engineering, both for practicing engineers and for students. The emphasis throughout is on concepts and basic principles. It contains practical applications to guide the reader to appreciate the value of each topic presented. This book was not developed to be used as a handbook or reference book; such books commonly are made up of a number of self-contained modules that provide information about separate topics. Rather, this work is a carefully woven fabric of connected ideas that are progressively developed. Handbooks and other ‘how to’ books are meant to meet short term needs for carrying out a given process but do not lead to a full understanding of the subject as is the goal here. More advanced texts are cited for further reading on the mathematical and statistical aspect of reliability analysis and engineering. |
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Elicitation of Expert Opinion for Uncertainty and Risks | Bilal Ayyub | 2001 | Experts, despite their importance and value, can be double-edged swords. They can make valuable contributions from their deep base of knowledge, but those contributions may also contain their own biases and pet theories. Therefore, selecting experts, eliciting their opinions, and aggregating their opinions must be performed and handled carefully, with full recognition of the uncertainties inherent in those opinions. Elicitation of Expert Opinions for Uncertainty and Risks illuminates those uncertainties and builds a foundation of philosophy, background, methods, and guidelines that helps its readers effectively execute the elicitation process. Based on the first-hand experiences of the author, the book is filled with illustrations, examples, case studies, and applications that demonstrate not only the methods and successes of expert opinion elicitation, but also its pitfalls and failures. |
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What Every Engineer Should Know About: Risk Engineering and Management |
John X. Wang |
2000 | Explains how to assess and handle technical risk, schedule risk, and cost risk efficiently and effectively--enabling engineering professionals to anticipate failures regardless of system complexity--highlighting opportunities to turn failure into success. |
1990-1999
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Introduction to the Physics of Materials | Aris Christou | 1999 | |
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Commercial Nuclear Power: Assuring Safety for the Future |
C. Ramsay |
1998 |
Describes the role that nuclear power could play as a viable option in meeting future electrical energy needs.
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Numerical Methods for Engineers |
Richard H. McCuen |
1995 | This book introduces numerical methods, emphasizing the practical aspects of their use and establishing their limitations, advantages, and disadvantages. It is intended to assist future as well as practicing engineers in fully understanding the fundamentals of numerical methods, most notably thier application, limitations and potentials. |
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Reliability of GaAs Monolithic Integrated Circuits |
W.T. Anderson |
1995 | |
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Integrating Reliability into Microcircuit Manufacturing | Aris Christou | 1994 | Explains and examines the principles, processes and materials of reliability manufacturing. The relationship between yield and reliability, requirements for the dual use electronics as the priority for the 90s, manufacturing and essential foundations of microcircuits, fabrication technology affecting microcircuit quality and reliability plus new technologies such as microelectromechanical systems, robotics and microwave integrated circuits are among the topics discussed. |
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Electromigration and Related Failure Mechanisms | Aris Christou | 1994 | Addresses electromigration failure modes in electronics covering both theory and experiments. Reviews silicon and GaAs technologies. Various rate controlling details are summarized including an investigation of temperature dependence. Concludes with a discussion regarding current status and future plans for electromigration resistant advanced metallization systems for VLSI. |
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What Every Engineer Should Know About: Reliability and Risk Analysis |
Marcel Dekker |
1993 | Examining reliability, availability, and risk analysis and reviewing in probability and statistics essential to understanding reliability methods, this outstanding volume describes day-to-day techniques used by practicing engineers--discussing important reliability aspects of both components and complex systems. |
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