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Recent Advances in System Reliability Engineering describes and evaluates the latest tools, techniques, strategies, and methods in this topic for a variety of applications. Special emphasis is put on simulation and modelling technology which is growing in influence in industry, and presents challenges as well as opportunities to reliability and systems engineers. Several manufacturing engineering applications are addressed, making this a particularly valuable reference for readers in that sector. Contains comprehensive discussions on state-of-the-art tools, techniques, and strategies from industry Connects the latest academic research to applications in industry including system reliability, safety assessment, and preventive maintenance Gives an in-depth analysis of the benefits and applications of modelling and simulation to reliability
Recent Advances in System Reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference. It describes the latest achievements in these fields, and covers the application of these achievements to reliability engineering practice. The chapters cover a wide range of new theoretical subjects and have been written by leading experts in reliability theory and its applications. The topics include: concepts and different definitions of signatures (D-spectra), their properties and applications to reliability of coherent systems and network-type structures; Lz-transform of Markov stochastic process and its application to multi-state system reliability analysis; methods for cost-reliability and cost-availability analysis of multi-state systems; optimal replacement and protection strategy; and statistical inference. Recent Advances in System Reliability presents many examples to illustrate the theoretical results. Real world multi-state systems, such as power generation and transmission, refrigeration, and production systems, are considered in the form of case studies, making the book a useful resource for researchers and postgraduate students.
This book addresses a modern topic in reliability: multi-state and continuous-state system reliability, which has been intensively developed in recent years. It offers an up-to-date overview of the latest developments in reliability theory for multi-state systems, engineering applications to a variety of technical problems, and case studies that will be of interest to reliability engineers and industrial managers. It also covers corresponding theoretical issues, as well as case studies illustrating the applications of the corresponding theoretical advances. The book is divided into two parts: Modern Mathematical Methods for Multi-state System Reliability Analysis (Part 1), and Applications and Case Studies (Part 2), which examines real-world multi-state systems. It will greatly benefit scientists and researchers working in reliability, as well as practitioners and managers with an interest in reliability and performability analysis. It can also be used as a textbook or as a supporting text for postgraduate courses in Industrial Engineering, Electrical Engineering, Mechanical Engineering, Applied Mathematics, and Operations Research.
This volume presents recent research in reliability and quality theory and its applications by many leading experts in the field. The subjects covered include reliability optimization, software reliability, maintenance, quality engineering, system reliability, Monte Carlo simulation, tolerance design optimization, manufacturing system estimation, neural networks, software quality assessment, optimization design of life tests, software quality, reliability-centered maintenance, multivariate control chart, methodology for measurement of test effectiveness, imperfect preventive maintenance, Markovian reliability modeling, accelerated life testing, and system availability assessment. The book will serve as a reference for postgraduate students and will also prove useful for practitioners and researchers in reliability and quality engineering. Sample Chapter(s). Chapter 1.1: Introduction (88 KB). Chapter 1.2: The Symmetrical Johnson Su Distributions (101 KB). Chapter 1.3: Application to Control Charts (79 KB). Chapter 1.4: An Example (84 KB). Chapter 1.5: How Kurtosis Affects Classical Charts (104 KB). Chapter 1.6: OC and ARL Curves (133 KB). Chapter 1.7: Conlusions (129 KB). Contents: Control Charts for Data Having a Symmetrical Distribution with a Positive Kurtosis (P Philippe); A Software Reliability Model with Testing Coverage and Imperfect Debugging (X Zhang & H Pham); Cost Allocation for Software Reliability (O Berman & M Cutler); General Reliability Test Plans for One-Shot Devices (W Zhang & W-K Shiue); Multivariate Control Chart (M-W Lu & R J Rudy); Optimal Preparedness Maintenance of Multi-Unit Systems with Imperfect Maintenance and Economic Dependence (H Wang et al.); Estimation of System Reliability by Variationally Processed Monte Carlo Simulation (M Chang et al.); A Bayesian Approach to the Optimal Policy under Imperfect Preventive Maintenance Models (K-S Park & C-H Jun); Design of Life Tests Based on Multi-Stage Decision Process (A Kanagawa & H Ohta); Reliability-Centered Maintenance for Light Rail Equipment (K H K Leung et al.); Incorporating Environmental Concepts with Tolerance Design Optimization Model (G Chen); Markovian Reliability Modeling for Software Safety/Availability Measurement (K Tokuno & S Yamada); Group Control Charts with Variable Stream and Sample Sizes (K T Lee et al.); A Methodology for the Measurement of Test Effectiveness (J C Munson & A P Nikora); Modeling Software Quality with Classification Trees (T M Khoshgoftaar & E B Allen); Highly Reliable Systems: Designing Software for Improved Assessment (B Cukic & F Bastani); Manufacturing Systems Estimation Using Neural Network Models (P L Cooper & G J Savage); A Deterministic Selective Maintenance Model for Complex Systems (C R Cassady et al.). Readership: Practitioners, postgraduate students and researchers in reliability and quality engineering.
This book presents original studies describing the latest research and developments in the area of reliability and systems engineering. It helps the reader identifying gaps in the current knowledge and presents fruitful areas for further research in the field. Among others, this book covers reliability measures, reliability assessment of multi-state systems, optimization of multi-state systems, continuous multi-state systems, new computational techniques applied to multi-state systems and probabilistic and non-probabilistic safety assessment.
The aim of this book is to provide a platform to academicians, practitioners, and researchers to understand current and future trends in software reliability growth modeling. Emphasis will be on qualitative work relevant to the theme with particular importance given to mathematical modeling for software reliability and various methods and applications of multi attributed decision making in governing the software performance. Presents software quality and security models Offers reliability analysis, assurance techniques for software systems Covers methodologies, tools, and practical applications of software reliability modeling and testing resources Includes robust reliability design techniques, diagnostic, and decision support Discusses stochastic modelling for software systems
Annotation This timely resource offers engineers and managers a comprehensive, unified treatment of the techniques and practice of systems reliability and failure prevention, without the use of advanced mathematics.
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 unique volume presents chapters written on the areas of life-testing and reliability by many well-known researchers who have contributed significantly to these two areas over the years. Chapters cover a wide range of topics such as inference under censoring and truncation, reliability growth models, designs to improve quality, prediction techniques, Bayesian analysis of reliability, multivariate methods, accelerated testing, and more. The book is written in an easy-to-follow style, first presenting the necessary theoretical details and then illustrating the methods with a numerical examples wherever possible. Many tables and graphs that are essential for the use of some of the new methodologies are presented throughout the volume. Numerous examples provide the reader with a clear understanding of the methods presented as well as with insight into the applications of these results.
This book provides the latest research advances in the field of system reliability assurance and engineering. It contains reference material for applications of reliability in system engineering, offering a theoretical sound background with adequate numerical illustrations. Included are concepts pertaining to reliability analysis, assurance techniques and methodologies, tools, and practical applications of system reliability modeling and allocation. The collection discusses various soft computing techniques like artificial intelligence and particle swarm optimization approach for reliability assessment. Importance of differentiating between the optimal release time and testing stop time of the software has been explicitly discussed and presented in the book. Features: Creates understanding of the costs associated with complex systems Covers reliability measurement of engineering systems Incorporates an efficient effort-based expenditure policy incorporating cost and reliability criteria Provides information for optimal testing stop and release time of software system Presents software performance and security layout Addresses reliability prediction and its maintenance through advanced analytics techniques Overall, System Reliability Management: Solutions and Techniques is a collaborative and interdisciplinary approach for better communication of problems and solutions to increase the performance of the system for better utilization and resource management.