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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
Complex high-technology devices are in growing use in industry, service sectors, and everyday life. Their reliability and maintenance is of utmost importance in view of their cost and critical functions. This book focuses on this theme and is intended to serve as a graduate-level textbook and reference book for scientists and academics in the field. The chapters are grouped into five complementary parts that cover the most important aspects of reliability and maintenance: stochastic models of reliability and maintenance, decision models involving optimal replacement and repair, stochastic methods in software engineering, computational methods and simulation, and maintenance management systems. This wide range of topics provides the reader with a complete picture in a self-contained volume.
This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
This book is a comprehensive guide to methodologies for analyzing reliability and optimizing maintenance in complex systems, spanning from initial design to operational stages. The book comprises 20 chapters, each addressing different research topics in the reliability and maintenance of complex systems. These chapters are authored by esteemed professors and researchers in the field of reliability engineering, and they are organized as follows: System Reliability Modeling (8 chapters), Optimal Maintenance Models (4 chapters), System Performance and Availability Analysis (3 chapters), and Reliability Testing and Accelerated Life Tests (2 chapters). The remaining chapters focus on reliability testing and life data analysis. The book offers an in-depth exploration of various techniques, algorithms, and practical industry applications, making it an invaluable resource for researchers engaged in system reliability analysis and maintenance optimization, as well as for practical engineers and industrial managers. This book will be useful to students, researchers, and engineers in understanding the latest research issues and techniques in reliability and maintenance engineering.
Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems. Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.
As our modern information-age society grows in complexity both in terms of embedded systems and applications, the problems and challenges in reliability become ever more complex. Bringing together many of the leading experts in the field, this volume presents a broad picture of current research on system modeling and optimization in reliability and its applications.The book comprises twenty-three chapters organized into four parts: Reliability Modeling, Software Quality Engineering, Software Reliability, and Maintenance and Inspection Policies. These sections cover a wide range of important topics, including system reliability modeling, optimization, software reliability and quality, maintenance theory and inspection, reliability failure analysis, sampling plans and schemes, software development processes and improvement, stochastic process modeling, statistical distributions and analysis, fault-tolerant performance, software measurements and cost effectiveness, queueing theory and applications, system availability, reliability of repairable systems, testing sampling inspection, software capability maturity model, accelerated life modeling, statistical control, and HALT testing.
Reliability Based Aircraft Maintenance Optimization and Applications presents flexible and cost-effective maintenance schedules for aircraft structures, particular in composite airframes. By applying an intelligent rating system, and the back-propagation network (BPN) method and FTA technique, a new approach was created to assist users in determining inspection intervals for new aircraft structures, especially in composite structures. This book also discusses the influence of Structure Health Monitoring (SHM) on scheduled maintenance. An integrated logic diagram establishes how to incorporate SHM into the current MSG-3 structural analysis that is based on four maintenance scenarios with gradual increasing maturity levels of SHM. The inspection intervals and the repair thresholds are adjusted according to different combinations of SHM tasks and scheduled maintenance. This book provides a practical means for aircraft manufacturers and operators to consider the feasibility of SHM by examining labor work reduction, structural reliability variation, and maintenance cost savings. - Presents the first resource available on airframe maintenance optimization - Includes the most advanced methods and technologies of maintenance engineering analysis, including first application of composite structure maintenance engineering analysis integrated with SHM - Provides the latest research results of composite structure maintenance and health monitoring systems
Availability of a system is a crucial factor for planning and optimization. The concept is more challenging for modern systems such as robots and autonomous systems consisting of a complex configuration of components. As complex systems have become global and essential in today’s society, their reliable design and the determination of their availability have turned into a very important task for managers and engineers. Reliability Models of Complex Systems for Robots and Automation offers different models and approaches for reliability evaluation and optimization of a complex autonomous system. Comprehensive fault tree analysis on the critical components of industrial robots and its integration with the reliability block diagram approach is designed in order to investigate the robot system reliability. The cost and hazard decision tree are integrated for the first time in an approach to evaluate the reliability of a complex system. Considers a complex production system composing of several autonomous robots Develops binary state reliability evaluation model for a complex system Introduces new concepts of hazard decision tree Proposes fault tree and reliability block diagram for complex robotic systems Develops stochastic process based reliability evaluation and optimization models Today’s competitive world with increasing customer demands for highly reliable products makes reliability engineering a more challenging task. Reliability analysis is one of the main tools to ensure agreed delivery deadlines which in turn maintains certainty in real tangible factors such as customer goodwill and company reputation.
This utterly comprehensive work is thought to be the first to integrate the literature on the physics of the failure of complex systems such as hospitals, banks and transport networks. It has chapters on particular aspects of maintenance written by internationally-renowned researchers and practitioners. This book will interest maintenance engineers and managers in industry as well as researchers and graduate students in maintenance, industrial engineering and applied mathematics.
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.