Recent Advances In Reliability Theory
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Recent Advances in Reliability Theory
Author: N. Limnios
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Conceiving reliablesystems is a strategic issue for any industrial society. Hence, reliability has become a discipline at the beginning of the Second World War. In fact, reliability is a field of reseach common to mathematics, operational research, informatics, graph theory, physics, and so forth. We are concerned here with the mathematical side of reliability, of which probability, statistics, and more specially stochastic processes theory constitute the natural basis. US army during the war, and later in the US Problems encountered by the and Soviet space programs, have led to an awarenessofthe need for reliabilityor more generaly for dependability (a general term covering reliability, availability, security, maintainability, etc.) of the systems. The paper by W. Weibull of 1938 on the strength of materials, leading to the distribution that later took his name, and the paper by B. Epstein and M. Sobel of 1951, initiating the use of the exponential distribution as the basic (and now most used) model for reliability, are the founding papers of the field. At this time, the systems were merely seen as black boxes. During the 1960s, they began to be considered as the result of the interaction of their elements. Appropriate methods were then developed, from Shannon's work to the beautiful theory of coherent systems initiated by Z.W. Birnbaum, J.D.
Recent Advances in Reliability and Quality Engineering
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.
Advances in System Reliability Engineering
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