|Author||: Mangey Ram,Hoang Pham|
|Release Date||: 2021-07-01|
|ISBN 10||: 0128233249|
|Pages||: 412 pages|
Safety and Reliability Modeling and Its Applications combines work by leading researchers in academia and industry, in engineering, statistics, and mathematics to provide innovative methods and solutions for this fast-moving field. Safety and reliability analysis is one of the most multidimensional topics in systems reliability engineering nowadays. Its rapid development has created many opportunities and challenges for both industrialists and academics, and has completely changed the global design and systems engineering environment. More of the modelling tasks can now be undertaken within a computer environment using simulation and virtual reality technologies, leading to an increase in the number and variety of research studies focusing on safety and reliability engineering. This book addresses these important recent developments, presenting new theoretical issues that were not previously presented in the literature, as well as solutions to important practical problems and case studies illustrating how to apply the methodology. Drawing on world-leading research from interdisciplinary authors, this book will help readers with a range of backgrounds to engage with this important topic, and find the solutions they need for their work. Uses case studies from industry practice to explain innovative solutions to real world safety and reliability problems Addresses the full interdisciplinary range of topics that influence this complex field Provides brief introductions to important concepts, including stochastic reliability, and Bayesian methods
Safety and Risk Modeling presents the latest theories and methods of safety and risk with an emphasis on safety and risk in modeling. It covers applications in several areas including transportations and security risk assessments, as well as applications related to current topics in safety and risk. Safety and Risk Modeling is a valuable resource for understanding the latest developments in both qualitative and quantitative methods of safety and risk analysis and their applications in operating environments. Each chapter has been written by active researchers or experienced practitioners to bridge the gap between theory and practice and to trigger new research challenges in safety and risk. Topics include: safety engineering, system maintenance, safety in design, failure analysis, and risk concept and modelling. Postgraduate students, researchers, and practitioners in many fields of engineering, operations research, management, and statistics will find Safety and Risk Modeling a state-of-the-art survey of reliability and quality in design and practice.
Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis • Structural Reliability • System Reliability, and • Uncertainty Analysis. Selected special sessions include contributions on: the Marie Skłodowska-Curie innovative training network in structural safety; risk approaches in insurance and fi nance sectors; dynamic reliability and probabilistic safety assessment; Bayesian and statistical methods, reliability data and testing; oganizational factors and safety culture; software reliability and safety; probabilistic methods applied to power systems; socio-technical-economic systems; advanced safety assessment methodologies: extended Probabilistic Safety Assessment; reliability; availability; maintainability and safety in railways: theory & practice; big data risk analysis and management, and model-based reliability and safety engineering. Safety and Reliability – Theory and Applications will be of interest to professionals and academics working in a wide range of industrial and governmental sectors including: Aeronautics and Aerospace, Automotive Engineering, Civil Engineering, Electrical and Electronic Engineering, Energy Production and Distribution, Environmental Engineering, Information Technology and Telecommunications, Critical Infrastructures, Insurance and Finance, Manufacturing, Marine Industry, Mechanical Engineering, Natural Hazards, Nuclear Engineering, Offshore Oil and Gas, Security and Protection, Transportation, and Policy Making.
Containing papers presented at the 18th European Safety and Reliability Conference (Esrel 2009) in Prague, Czech Republic, September 2009, Reliability, Risk and Safety Theory and Applications will be of interest for academics and professionals working in a wide range of industrial and governmental sectors, including Aeronautics and Aerospace, Aut
|Author||: Hoang Pham|
|Publisher||: World Scientific|
|Release Date||: 2001|
|ISBN 10||: 9789812811868|
|Pages||: 344 pages|
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.
Presents the theory and methodology for reliabilityassessments of safety-critical functions through examples from awide range of applications Reliability of Safety-Critical Systems: Theory andApplications provides a comprehensive introduction toreliability assessments of safety-related systems based onelectrical, electronic, and programmable electronic (E/E/PE)technology. With a focus on the design and development phases ofsafety-critical systems, the book presents theory and methodsrequired to document compliance with IEC 61508 and the associatedsector-specific standards. Combining theory and practical applications, Reliability ofSafety-Critical Systems: Theory and Applications implements keysafety-related strategies and methods to meet quantitative safetyintegrity requirements. In addition, the book details a variety ofreliability analysis methods that are needed during all stages of asafety-critical system, beginning with specification and design andadvancing to operations, maintenance, and modification control. Thekey categories of safety life-cycle phases are featured, includingstrategies for the allocation of reliability performancerequirements; assessment methods in relation to design; andreliability quantification in relation to operation andmaintenance. Issues and benefits that arise from complex moderntechnology developments are featured, as well as: Real-world examples from large industry facilities with majoraccident potential and products owned by the general public such ascars and tools Plentiful worked examples throughout that provide readers witha deeper understanding of the core concepts and aid in the analysisand solution of common issues when assessing all facets ofsafety-critical systems Approaches that work on a wide scope of applications and can beapplied to the analysis of any safety-critical system A brief appendix of probability theory for reference With an emphasis on how safety-critical functions are introducedinto systems and facilities to prevent or mitigate the impact of anaccident, this book is an excellent guide for professionals,consultants, and operators of safety-critical systems who carry outpractical, risk, and reliability assessments of safety-criticalsystems. Reliability of Safety-Critical Systems: Theory andApplications is also a useful textbook for courses inreliability assessment of safety-critical systems and reliabilityengineering at the graduate-level, as well as for consultingcompanies offering short courses in reliability assessment ofsafety-critical systems.
|Author||: Amit Kumar,Mangey Ram|
|Publisher||: Academic Press|
|Release Date||: 2021-01-09|
|ISBN 10||: 0128231580|
|Pages||: 520 pages|
The Handbook of Reliability, Maintenance, and System Safety through Mathematical Modeling discusses the many factors affect reliability and performance, including engineering design, materials, manufacturing, operations, maintenance, and many more. Reliability is one of the fundamental criteria in engineering systems design, with maintenance serving as a way to support reliability throughout a system’s life. Addressing these issues requires information, modeling, analysis and testing. Different techniques are proposed and implemented to help readers analyze various behavior measures (in terms of the functioning and performance) of systems. Enables mathematicians to convert any process or system into a model that can be analyzed through a specific technique Examines reliability and mathematical modeling in a variety of disciplines, unlike competitors which typically examine only one Includes a table of contents with simple to complex examples, starting with basic models and then refining modeling approaches step-by-step
|Author||: P. Thoft-Cristensen,M.J. Baker|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2012-12-06|
|ISBN 10||: 3642686974|
|Pages||: 268 pages|
Structural reliability theory is concerned with the rational treatment of uncertainties in struc tural engineering and with the methods for assessing the safety and serviceability of civil en gineering and other structures. It is a subject which has grown rapidly during the last decade and has evolved from being a topic for academic research to a set of well-developed or develop ing methodologies with a wide range of practical applications. Uncertainties exist in most areas of civil and structural engineeri'1.g and rational design decisions cannot be made without modelling them and taking them into account. Many structural en gineers are shielded from having to think about such problems, at least when designing simple structures, because of the prescriptive and essentially deterministic nature of most codes of practice. This is an undesirable situation. Most loads and other structural design parameters are rarely known with certainty and should be regarded as random variables or stochastic processes, even if in design calculations they are eventually treated as deterministic. Some problems such as the analysis of load combinations cannot even be formulated without recourse to probabilistic reasoning.
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
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Reliability and safety are core issues that must be addressed throughout the life cycle of engineering systems. Reliability and Safety Engineering presents an overview of the basic concepts, together with simple and practical illustrations. The authors present reliability terminology in various engineering fields, viz., • electronics engineering, • software engineering, • mechanical engineering, • structural engineering, and • power systems engineering. They describe the latest applications in the area of probabilistic safety assessment, such as technical specification optimization, risk monitoring and risk informed in-service inspection. Reliability and safety studies must, inevitably, deal with uncertainty, so the book includes uncertainty propagation methods: Monte Carlo simulation, fuzzy arithmetic, Dempster-Shafer theory and probability bounds. Reliability and Safety Engineering also highlights advances in system reliability and safety assessment including dynamic system modeling and uncertainty management. Case studies from typical nuclear power plants, as well as from structural, software, and electronic systems are also discussed. Reliability and Safety Engineering combines discussions of the existing literature on basic concepts and applications with state-of-the-art methods used in reliability and risk assessment of engineering systems. It is designed to assist practicing engineers, students and researchers in the areas of reliability engineering and risk analysis.
Software reliability is one of the most important characteristics of software product quality. Its measurement and management technologies during the software product life cycle are essential to produce and maintain quality/reliable software systems. Part 1 of this book introduces several aspects of software reliability modeling and its applications. Hazard rate and nonhomogeneous Poisson process (NHPP) models are investigated particularly for quantitative software reliability assessment. Further, imperfect debugging and software availability models are discussed with reference to incorporating practical factors of dynamic software behavior. Three software management problems are presented as application technologies of software reliability models: the optimal software release problem, the statistical testing-progress control, and the optimal testing-effort allocation problem. Part 2 of the book describes several recent developments in software reliability modeling and their applications as quantitative techniques for software quality/reliability measurement and assessment. The discussion includes a quality engineering analysis of human factors affecting software reliability during the design review phase, which is the upper stream of software development, as well as software reliability growth models based on stochastic differential equations and discrete calculus during the testing phase, which is the lower stream. The final part of the book provides an illustration of quality-oriented software management analysis by applying the multivariate analysis method and the existing software reliability growth models to actual process monitoring data.