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This book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems. Drawing on the authors’ extensive experience within the field of reliability engineering, it addresses and discusses a variety of topics, including: • Background and overview of safety and dependability studies; • Explanation and critical analysis of definitions related to core concepts; • Risk identification through qualitative approaches (preliminary hazard analysis, HAZOP, FMECA, etc.); • Modelling of industrial systems through static (fault tree, reliability block diagram), sequential (cause-consequence diagrams, event trees, LOPA, bowtie), and dynamic (Markov graphs, Petri nets) approaches; • Probabilistic calculations through state-of-the-art analytical or Monte Carlo simulation techniques; • Analysis, modelling, and calculations of common cause failure and uncertainties; • Linkages and combinations between the various modelling and calculation approaches; • Reliability data collection and standardization. The book features illustrations, explanations, examples, and exercises to help readers gain a detailed understanding of the topic and implement it into their own work. Further, it analyses the production availability of production systems and the functional safety of safety systems (SIL calculations), showcasing specific applications of the general theory discussed. Given its scope, this book is a valuable resource for engineers, software designers, standard developers, professors, and students.
The authors present an elementary and exceptionally lucid introduction to issues in measurement theory. They define and discuss validity and reliability; proceed to a discussion of three basic types of validity, including criterion, content, and construct validity; present an introductory discussion of classical test theory, with an emphasis on parallel measures; and present a clear discussion of four methods of reliability estimation, including the test-retest, alternative form, split-half, and internal consistency methods of reliability assessment. The text is concluded with a discussion of the use of reliability assessment for purposes of correcting bivariate correlations for attenuation due to random measurement error.
This open access book describes and reviews the development of the quality control mechanisms and methodologies associated with IEA’s extensive program of educational research. A group of renowned international researchers, directly involved in the design and execution of IEA’s international large-scale assessments (ILSAs), describe the operational and quality control procedures that are employed to address the challenges associated with providing high-quality, comparable data. Throughout the now considerable history of IEA’s international large-scale assessments, establishing the quality of the data has been paramount. Research in the complex multinational context in which IEA studies operate imposes significant burdens and challenges in terms of the methodologies and technologies that have been developed to achieve the stated study goals. The demands of the twin imperatives of validity and reliability must be satisfied in the context of multiple and diverse cultures, languages, orthographies, educational structures, educational histories, and traditions. Readers will learn about IEA’s approach to such challenges, and the methods used to ensure that the quality of the data provided to policymakers and researchers can be trusted. An often neglected area of investigation, namely the consequential validity of ILSAs, is also explored, examining issues related to reporting, dissemination, and impact, including discussion of the limits of interpretation. The final chapters address the question of the influence of ILSAs on policy and reform in education, including a case study from Singapore, a country known for its outstanding levels of achievement, but which nevertheless seeks the means of continual improvement, illustrating best practice use of ILSA data.
We are very pleased to be asked to co-author this book for a variety of reasons, one of which was that it gave us further opportunity to work together. The scope proposed was very wide with the only significant proviso being that the book should be in a mongraph-style and not a teaching text. This require ment has given us the opportunity to compile a wide range of relevant material relating to present-day knowledge and application in power system reliability. As many readers will be aware, we have collaborated in many ways over a relatively long period and have co-authored two other books on reliability evaluation. Both of these previous books were structured as teaching texts. This present book is not a discourse on "how to do reliability evaluation" but a discussion on "why it should be done and what can be done and achieved" and as such does not replace or conflict with the previous books. The three books are complementary and each enhances the others. The material contained in this book is not specifically original since it is based on information which we have published in other forms either jointly or as co authors with various other people, particularly our many research students. We sincerely acknowledge the important contributions made by all these students and colleagues. There are too many to mention individually in this preface but their names appear frequently in the references at the end of each chapter.
The application of quantitative reliability evaluation in electric power sys tems has now evolved to the point at which most utilities use these techniques in one or more areas of their planning, design, and operation. Most of the techniques in use are based on analytical models and resulting analytical evaluation procedures. Improvements in and availability of high-speed digi tal computers have created the opportunity to analyze many of these prob lems using stochastic simulation methods and over the last decade there has been increased interest in and use made of Monte Carlo simulation in quantitative power system reliability assessment. Monte Carlo simulation is not a new concept and recorded applications have existed for at least 50 yr. However, localized high-speed computers with large-capacity storage have made Monte Carlo simulation an available and sometimes preferable option for many power system reliability applications. Monte Carlo simulation is also an integral part of a modern undergrad uate or graduate course on reliability evaluation of general engineering systems or specialized areas such as electric power systems. It is hoped that this textbook will help formalize the many existing applications of Monte Carlo simulation and assist in their integration in teaching programs. This book presents the basic concepts associated with Monte Carlo simulation.
The importance of power system reliability is demonstrated when our electricity supply is disrupted, whether it decreases the comfort of our free time at home or causes the shutdown of our companies and results in huge economic deficits. The objective of Assessment of Power System Reliability is to contribute to the improvement of power system reliability. It consists of six parts divided into twenty chapters. The first part introduces the important background issues that affect power system reliability. The second part presents the reliability methods that are used for analyses of technical systems and processes. The third part discusses power flow analysis methods, because the dynamic aspect of a power system is an important part of related reliability assessments. The fourth part explores various aspects of the reliability assessment of power systems and their parts. The fifth part covers optimization methods. The sixth part looks at the application of reliability and optimization methods. Assessment of Power System Reliability has been written in straightforward language that continues into the mathematical representation of the methods. Power engineers and developers will appreciate the emphasis on practical usage, while researchers and advanced students will benefit from the simple examples that can facilitate their understanding of the theory behind power system reliability and that outline the procedure for application of the presented methods.
This book presents a systematic approach in performing reliability assessment of solder joints using Finite Element (FE) simulation. Essential requirements for FE modelling of an electronic package or a single reflowed solder joint subjected to reliability test conditions are elaborated. These cover assumptions considered for a simplified physical model, FE model geometry development, constitutive models for solder joints and aspects of FE model validation. Fundamentals of the mechanics of solder material are adequately reviewed in relation to FE formulations. Concept of damage is introduced along with deliberation of cohesive zone model and continuum damage model for simulation of solder/IMC interface and bulk solder joint failure, respectively. Applications of the deliberated methodology to selected problems in assessing reliability of solder joints are demonstrated. These industry-defined research-based problems include solder reflow cooling, temperature cycling and mechanical fatigue of a BGA package, JEDEC board-level drop test and mechanisms of solder joint fatigue. Emphasis is placed on accurate quantitative assessment of solder joint reliability through basic understanding of the mechanics of materials as interpreted from results of FE simulations. The FE simulation methodology is readily applicable to numerous other problems in mechanics of materials and structures.
Reliability Assessment and Optimization of Complex Systems delves into a range of tools and techniques for designing optimized complex systems. Each chapter explores system modeling and the implementation of various metaheuristics for optimization purposes. This book provides readers in the domain of applied mathematics with a comprehensive understanding of system reliability analysis and improvement, thereby offering substantial value to their knowledge and expertise. System reliability has become the paramount attribute of any production unit. The process of maximizing system reliability while adhering to multiple constraints is referred to as reliability optimization.There are two primary approaches to enhancing a system's performance and reliability: developing a product with reduced failures (failure avoidance) or incorporating resilience to ensure the system continues functioning even in the event of a failure (fault tolerance). - Explains the process and application of reliability-based design optimization - Covers many metaheuristic approaches such as reliability, cost, and the MTTF of the system - Provides the workings and applications of multi-objective optimizations
Human error is here to stay. This perhaps obvious statement has a profound implication for society when faced with the types of hazardous system accidents that have occurred over the past three decades. Such accidents have been strongly influenced by human error, yet many system designs in existence or being planned and built do not take human error into consideration.; "A Guide to Practical Human Reliability Assessment" is a practical and pragmatic guide to the techniques and approaches of human reliability assessment HRA. lt offers the reader explanatory and practical methods which have been applied and have worked in high technology and high risk assessments - particularly but not exclusively to potentially hazardous industries such as exist in process control, nuclear power, chemical and petrochemical industries. A Guide to Practical Human Reliability Assessment offers the practitioner a comprehensive tool-kit of different approaches along with guidance on selecting different methods for different applications. It covers the risk assessment and the HRA process, as well as methods of task analysis, error identification, quantification, representation of errors in the risk analysis, followed by error reduction analysis, quality assurance and documentation. There are also a number of detailed case studies from nuclear, chemical, offshore, and marine HRA'S, exemplfying the image of techniques and the impact of HRA in existing and design-stage systems.
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.