Reliability And Risk Models

This book describes a radically new approach and technology for setting reliability requirements based on minimum failure-free operating periods (MFFOP technology). It covers how systems characterized by high cost (consequences) of failure, to develop reliability analysis driven by the consequences of failure.

“Failure Rate Modeling for Reliability and Risk” focuses on reliability theory, and to the failure rate (hazard rate, force of mortality) modeling and its generalizations to systems operating in a random environment and to repairable systems. The failure rate is one of the crucial probabilistic characteristics for a number of disciplines; including reliability, survival analysis, risk analysis and demography. The book presents a systematic study of the failure rate and related indices, and covers a number of important applications where the failure rate plays the major role. Applications in engineering systems are studied, together with some actuarial, biological and demographic examples. The book provides a survey of this broad and interdisciplinary subject which will be invaluable to researchers and advanced students in reliability engineering and applied statistics, as well as to demographers, econometricians, actuaries and many other mathematically oriented researchers.

A comprehensively updated and reorganized new edition. The updates include comparative methods for improving reliability; methods for optimal allocation of limited resources to achieve a maximum risk reduction; methods for improving reliability at no extra cost and building reliability networks for engineering systems. Includes: A unique set of 46 generic principles for reducing technical risk Monte Carlo simulation algorithms for improving reliability and reducing risk Methods for setting reliability requirements based on the cost of failure New reliability measures based on a minimal separation of random events on a time interval Overstress reliability integral for determining the time to failure caused by overstress failure modes A powerful equation for determining the probability of failure controlled by defects in loaded components with complex shape Comparative methods for improving reliability which do not require reliability data Optimal allocation of limited resources to achieve a maximum risk reduction Improving system reliability based solely on a permutation of interchangeable components

Analysis of reliability and risk is an important and integral part of planning, construction and operation of all technical systems. To be able to perform such analyses systematically and scientifically, there is usually a need for special methods and models. This book presents the most important of these. Particular emphasis has been placed on the ideas and the motivation for the use of the various methods and models. It has been an objective to compile a book which provides practising engineers and engineering graduates with the concepts and basic techniques for evaluating reliability and risk. It is hoped that the material presented will make them so familiar with the subject that they can carry out various types of analyses themselves and understand and make use of the more detailed applications and additional material which is available in the journals and publications associated with their own discipline. It has also been an objective to put reliability and risk analyses in context - how such analyses should be used in design and operation of components and systems. The material presented is modern and a large part of the book is at research level. The book focuses on analysis of repairable systems, not only non-repairable systems which have traditionally been given most attention in textbooks on reliability theory. Since most real-life systems are repairable, methods for analysing repairable systems are an important area of research. The book presents general methods, with most applications taken from offshore petro leum activities.

This book addresses reliability, maintenance, risk, and safety issues of industrial systems with applications of the latest decision-making techniques. Thus, this book presents chapters that apply advanced tools, techniques, and computing models for optimizing the performance of industrial and manufacturing systems, along with other complex engineering equipment. Computing techniques like data analytics, failure mode and effects analysis, fuzzy set theory, petri-net, multi-criteria decision-making (MCDM), and soft computing are used for solving problems of reliability, risk, and safety related issues.

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.

An introduction to the MFFOP and cost-of-failure based approaches to reliability analysis and its applications. For many production systems it is important to guarantee a small risk of violating specified minimum failure-free operating periods before random failures. This is dictated by the high cost of failure and the intervention for repair. Reliability and Risk Models describes radically new approaches for setting quantitative reliability requirements based on the cost of failure and specified minimum failure-free operating periods (MFFOP). The cost-of-failure based reliability analysis provides a real alternative to the current reliability analysis disconnected from the cost of failure. Beginning with a comprehensive introduction to reliability and risk analysis based on random variables, this book: Examines a new methodology for problem solving in the context of real reliability engineering problems. Demonstrates the new reliability methodology through a number of practical applications and case studies. Supplies the code of the algorithms which can be used for reliability analyses and setting quantitative reliability requirements. Gives a comprehensive overview of basic Monte Carlo simulation techniques and algorithms for solving reliability engineering problems. In addition, this book provides a comprehensive introduction to load-strength interference models for reliability and risk analysis by introducing the overstress reliability integral: a generalisation of the load-strength interference integral with the time included. Furthermore, an efficient model for determining the probability of failure of loaded components and structures with internal flaws is also presented. Reliability and Risk Models is essential reading for practising engineers, researchers and consultants dealing with reliability and risk assessment. Lecturers and graduate students involved in reliability engineering will also find it an excellent reference and it is a useful tool for actuaries, economists and lecturers in applied probability and statistics.

This book integrates multiple criteria concepts and methods for problems within the Risk, Reliability and Maintenance (RRM) context. The concepts and foundations related to RRM are considered for this integration with multicriteria approaches. In the book, a general framework for building decision models is presented and this is illustrated in various chapters by discussing many different decision models related to the RRM context. The scope of the book is related to ways of how to integrate Applied Probability and Decision Making. In Applied Probability, this mainly includes: decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. In Decision Making, it includes a broad range of topics in MCDM (Multi-Criteria Decision Making) and MCDA (Multi-Criteria Decision Aiding; also known as Multi-Criteria Decision Analysis). In addition to decision analysis, some of the topics related to Mathematical Programming area are briefly considered, such as multiobjective optimization, since methods related to these topics have been applied to the context of RRM. The book addresses an innovative treatment for the decision making in RRM, thereby improving the integration of fundamental concepts from the areas of both RRM and decision making. This is accomplished by presenting an overview of the literature on decision making in RRM. Some pitfalls of decision models when applying them to RRM in practice are discussed and guidance on overcoming these drawbacks is offered. The procedure enables multicriteria models to be built for the RRM context, including guidance on choosing an appropriate multicriteria method for a particular problem faced in the RRM context. The book also includes many research advances in these topics. Most of the multicriteria decision models that are described are specific applications that have been influenced by this research and the advances in this field. Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis is implicitly structured in three parts, with 12 chapters. The first part deals with MCDM/A concepts methods and decision processes. The second part presents the main concepts and foundations of RRM. Finally the third part deals with specific decision problems in the RRM context approached with MCDM/A models.