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This book provides an application-oriented framework for reliability modeling and analysis of repairable systems in conjunction with the procurement process of weapon systems and throughput analysis for industries. Most of the reliability literature is directed towards non-repairable systems, that is, systems that fail are discarded or replaced. This book is mainly dedicated towards providing coverage to the reliability modeling and analysis of repairable systems that undergo failure-repair cycles. This unique book provides a comprehensive framework for the modeling and analysis of repairable systems considering both the non-parametric and parametric approaches to deal with their failure data. The book presents MCF based non-parametric approach with several illustrative examples and the generalized renewal process (GRP) based arithmetic reduction of age (ARA) models along with its applications to the systems failure data from the aviation industry. A complete chapter on an integrated framework for procurement process is devoted by utilizing the concepts of multi-criteria decision-making (MCDM) techniques which will of a great assistance to the readers in enhancing the potential of their respective organizations. This book also presents FMEA methods tailored for GRP based repairs. This text has primarily emerged from the industrial experience and research work of the authors. A number of illustrations have been included to make the subject lucid and vivid even to the readers who are relatively new to this area. Besides, various examples have been provided to display the applicability of presented models and methodologies to assist the readers in applying the concepts presented in this book.
This study is concerned with the reliability analysis of commonly used repairable and non-repairable redundant systems (with common-cause failures) such as parallel, k-out-of-n and standby with identical and non-identical units. Formulas for steady state system availability, system reliability and system mean time to failure are developed. The variation of steady state system availability, system reliability and system mean time to failure with common-cause failures is shown by means of plots for the above mentioned configurations. This study clearly shows that the occurrence of common-cause failures has a negative effect on system reliability parameters.
In the past, many catastrophic failures have occurred due to lack of redundancy and managerial oversight. For example, it was found that local failures due to improper welds that connected the suspended truss to the anchor trusses caused the collapse of the Grand Sung-Soo Bridge in Seoul, South Korea on October 21, 1994. Due to a lack of structural redundancy, the initial bridge rib failure was followed by other bridge failures leading to system collapse. With proper system reliability analysis, such cascading failures could be foreseen by stakeholders. To help make better risk-informed decisions, system reliability methods have been developed to analyze general structures subjected to the risk of cascading system-level failures caused by local fatigue-induced failures. For efficient reliability analysis of such complex system problems, many research efforts have been made to identify critical failure sequences with significant likelihoods by an event-tree search coupled with system reliability analyses: however, this approach is time-consuming or intractable due to repeated calculations of the probabilities of innumerable failure modes, which often necessitates using heuristic assumptions or simplifications. Recently, a decoupled approach was proposed: critical failure modes are first identified in the space of random variables without system reliability analyses or an event-tree search, then an efficient system reliability analysis was performed to compute the system failure probability based on the identified modes. In order to identify critical failure modes in the decreasing order of their relative contributions to the system failure probability, a simulation-based selective searching technique was developed by use of a genetic algorithm. The system failure probability was then computed by a multi-scale system reliability method that can account for the statistical dependence among the component events as well as among the identified failure modes. Part of this work presents this decoupled approach in detail and demonstrates its applicability to complex bridge structural systems that are subjected to the risk of cascading failures induced by fatigue. Using a recursive formulation for describing limit-states of local fatigue cracking, the system failure event is described as a disjoint cut-set event. Critical cut-sets, i.e. failure sequences with significant likelihood are identified by the selective searching technique using a genetic algorithm. Then, the probabilities of the cut-sets are computed by use of crude Monte Carlo simulations. Owing to the mutual exclusiveness of the cut-sets, the lower-bound on the system cascading failure probability is obtained by a simple addition of the cut-set probabilities. A numerical example of a bridge structure demonstrates that the proposed search method skillfully identifies the dominant failure modes contributing most to the system failure probability, and the system reliability analysis method accurately evaluates the system failure probability with statistical dependence fully considered. An example bridge with approximately 100 truss elements is considered to investigate the applicability of the method to realistic large-size structures. The efficiency and accuracy of the method are demonstrated through comparison with Monte Carlo simulations. The aforementioned system reliability analysis is based off of an a priori inspection cycle time and computes the probability that the time until the system failure is smaller than the given inspection cycle. Since most field practitioners do not know this value beforehand, a new method has been developed to perform simplified reliability analysis for many performance levels simultaneously. The First-Order Reliability Method (FORM) is often used for structural reliability analysis. The proposed method uses a multi-objective genetic algorithm, called Non-dominated based Sorting Genetic Algorithm II (NSGA II) to perform many FORM analyses simultaneously to generate a Pareto Surface of design points. From this Pareto surface, data on cases of 0́−critical but unlikely failures0́+ for short inspection cycle times and cases of 0́−less-critical but highly likely failures0́+ for long inspection cycle times can be found at once. From the nature of this method, this approach is termed as 0́−Multi-Objective0́+ FORM. Part of this work presents this Multi-objective FORM in detail. The applicability of this approach is shown through two numerical examples. The first example is a general situation with few random variables. The second example analyzes a statically indeterminate truss subjected to cyclic loading. Both numerical examples are validated with crude-MCS results and show that the method can find a full Pareto Surface, which provides reliability analysis results at a range of performance levels along with the probability distribution of the performance quantity.
Tools to Proactively Predict Failure The prediction of failures involves uncertainty, and problems associated with failures are inherently probabilistic. Their solution requires optimal tools to analyze strength of evidence and understand failure events and processes to gauge confidence in a design’s reliability. Reliability Engineering and Risk Analysis: A Practical Guide, Second Edition has already introduced a generation of engineers to the practical methods and techniques used in reliability and risk studies applicable to numerous disciplines. Written for both practicing professionals and engineering students, this comprehensive overview of reliability and risk analysis techniques has been fully updated, expanded, and revised to meet current needs. It concentrates on reliability analysis of complex systems and their components and also presents basic risk analysis techniques. Since reliability analysis is a multi-disciplinary subject, the scope of this book applies to most engineering disciplines, and its content is primarily based on the materials used in undergraduate and graduate-level courses at the University of Maryland. This book has greatly benefited from its authors' industrial experience. It balances a mixture of basic theory and applications and presents a large number of examples to illustrate various technical subjects. A proven educational tool, this bestselling classic will serve anyone working on real-life failure analysis and prediction problems.
Recent advances in science and technology have made modern computing and engineering systems more powerful and sophisticated than ever. The increasing complexity and scale imply that system reliability problems not only continue to be a challenge but also require more efficient models and solutions. This is the first book systematically covering the state-of-the-art binary decision diagrams and their extended models, which can provide efficient and exact solutions to reliability analysis of large and complex systems. The book provides both basic concepts and detailed algorithms for modelling and evaluating reliability of a wide range of complex systems, such as multi-state systems, phased-mission systems, fault-tolerant systems with imperfect fault coverage, systems with common-cause failures, systems with disjoint failures, and systems with functional dependent failures. These types of systems abound in safety-critical or mission-critical applications such as aerospace, circuits, power systems, medical systems, telecommunication systems, transmission systems, traffic light systems, data storage systems, and etc. The book provides both small-scale illustrative examples and large-scale benchmark examples to demonstrate broad applications and advantages of different decision diagrams based methods for complex system reliability analysis. Other measures including component importance and failure frequency are also covered. A rich set of references is cited in the book, providing helpful resources for readers to pursue further research and study of the topics. The target audience of the book is reliability and safety engineers or researchers. The book can serve as a textbook on system reliability analysis. It can also serve as a tutorial and reference book on decision diagrams, multi-state systems, phased-mission systems, and imperfect fault coverage models.
Safety and Reliability – Safe Societies in a Changing World collects the papers presented at the 28th European Safety and Reliability Conference, ESREL 2018 in Trondheim, Norway, June 17-21, 2018. The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk management Safety and Reliability – Safe Societies in a Changing World will be invaluable to academics and professionals working in a wide range of industrial and governmental sectors: offshore oil and gas, nuclear engineering, aeronautics and aerospace, marine transport and engineering, railways, road transport, automotive engineering, civil engineering, critical infrastructures, electrical and electronic engineering, energy production and distribution, environmental engineering, information technology and telecommunications, insurance and finance, manufacturing, marine transport, mechanical engineering, security and protection, and policy making.
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
Ernst G. Frankel This book has its origin in lecture notes developed over several years for use in a course in Systems Reliability for engineers concerned with the design of physical systems such as civil structures, power plants, and transport vehicles of all types. Increasing public concern with the reliability o~ systems for reasons of human safety, environmental protection, and acceptable ir. vestment risk limitations has resulted in an increasing interest by engineers in the formal applica~i0n of reliability theory to e~gineering desian. At the same time there is a demand for more effective approaches to the des~gn of procedures for the operation and use of man-made syste~s and more meaningful assessment of the risks intr)duction and use of such a system poses both when operating as designed and when operating at below design performance. The purpose of the book is to provide a sound, yet practical, introduction to reliability analysis and risk assessment which can be used by professionals in engineering, planning, management, and economics to improve the design, operation, and risk assessment of systems of interest. The text should be useful for students in many disciplines and is designed for fourth~year undergraduates or first-year graduate students. I would like to acknowledge the help of many of my graduate students who contributed to the development of this book by offering comments and criticism. Similarly I would like to thank Mrs.