Reliability modeling, analysis and optimization

Cover of: Reliability modeling, analysis and optimization |

Published by World Scientific in Singapore .

Written in English

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Edition Notes

Book details

Statement[edited by] Hoang Pham.
Classifications
LC ClassificationsTA
The Physical Object
Paginationxviii, 487 p. :
Number of Pages487
ID Numbers
Open LibraryOL22744656M
ISBN 109812563881

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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 book comprises twenty-three chapters organized into four parts: Reliability Modeling, Software Quality Engineering, Software Reliability, and Maintenance Cited by: 9.

Reliability Modeling, Analysis and Optimization. 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.

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. This volume presents current research and system modeling and optimization in reliability and its applications by many leading experts in the field.

The book comprised of twenty-three chap-ters, organized in four parts: Reliability Modeling, Software Quality Engineering, Software Reliability Modeling, and Maintenance and Inspection Policies. Bringing together business and engineering to reliability analysis With manufactured products exploding in numbers and complexity, reliability studies play an increasingly critical role throughout a products entire life cycle-from design to post-sale support.

Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and.

Bringing together business and engineering to reliability analysis With manufactured products exploding in numbers and complexity, reliability studies play an increasingly critical role throughout a product's entire life cycle-from design to post-sale support.

Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and Reviews: 1. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data.

Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and commercial aspects of product reliability, integrating concepts and methodologies from such diverse areas as engineering, materials science, statistics, probability, operations research, and management.

Blischke, W. R., et al. [14] described the prediction and optimization through modeling for reliability analysis. Studies were conducted to predict and optimize building energy related fields. The surrogate model techniques, such as the responses surface method, artificial neural networks, polynomial chaos, and Kriging method, have been proposed for engineering problems, i.e., reliability analysis of aircraft structures, stability analysis of soil slope, optimization design of composite structures and stochastic dynamic.

Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and commercial aspects of product reliability, integrating concepts and methodologies from such diverse areas as engineering, materials science, statistics, probability, operations research, and by:   Recent developments in reliability engineering has become the most challenging and demanding area of research.

Modeling and Simulation, along with System Reliability Engineering has become a greater issue because of high-tech industrial processes, using more complex systems today.

This book gives the latest research advances in the field of modeling and simulation, based on analysis. CHAPTER 3 Collection and Preliminary Analysis of Failure Data INTRODUCTION In Chapter 1, the two concepts most important to this book, failure and reliability, were introduced.

There are - Selection from Reliability: Modeling, Prediction, and Optimization [Book]. ISBN: X: OCLC Number: Description: 1 online resource (xviii, pages): illustrations. Contents: 1. Numerical computation of the marginal distributions of a semi-Markov process / C.

Cocozza-Thivent and R. Eymard Optimal checkpointing interval for task duplication with spare processing / S. Nakagawa, Y. Okuda and S. Yamada Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and commercial aspects of product reliability, integrating concepts and methodologies from such diverse areas as engineering, materials science, statistics, probability, operations research, and management.

In this paper, we considered reliability modeling and condition-based maintenance optimization of a critical equipment that installs a two-unit warm standby cooling system to control its temperature.

The influence of coolers’ working conditions on the degradation process of a critical system is investigated, and accordingly several failure. Reliability Engineering Reference Books recommended by ReliaSoft. Accelerated Testing: Statistical Models, Test Plans and Data Analyses (Wiley Series in Probability and Mathematical Statistics-Applied Probability), by Wayne Nelson, Published Analysis of Failure and Survival Data, by Peter J.

Smith, Published ; Applied Life Data Analysis, by Wayne Nelson, Published The book presents a collection of chapters dealing with a wide selection of topics concerning different applications of modeling.

It includes modeling, simulation and optimization applications in the areas of medical care systems, genetics, business, ethics and linguistics, applying very sophisticated methods.

Algorithms, 3-D modeling, virtual reality, multi objective optimization, finite. In recent years, a lot of novelties were developed compared to what is done over the word, such as the Weibull-Markov modeling in data analysis, nonparametric distributions in switching components behavior, Box and Jenkins models in blackouts forecasting and reliability aspects in smart grids development and multicriteria optimization.

Presents a cross-layer approach to transistor aging modeling, analysis and mitigation, spanning multiple abstraction levels; Equips readers for EM-induced dynamic reliability management and energy or lifetime optimization techniques, for many-core dark silicon microprocessors, embedded systems, lower power many-core processors and : Springer International Publishing.

His current research interests include various aspects of reliability, maintenance, warranties and service contracts. He has authored or co-authored 20 book chapters, journal papers and conference papers.

He is a co-author of 7, and co-editor of 3, books. This book equips the reader with a compact information source on all the most recent methodological tools available in the area of reliability prediction and analysis. Topics covered include reliability mathematics, organisation and analysis of data, reliability modelling and system reliability.

This paper investigates the use of the efficient global optimization and efficient global reliability analysis methods to construct surrogate models at both the design optimization and reliability analysis levels to create methods that are more efficient than existing methods without sacrificing accuracy.

Most of the multicriteria decision models that are described are specific applications that have been influenced by this research and the advances in this field. Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis is implicitly structured in three parts, with 12 chapters.

The first part deals with. We also develop an important understanding of how modeling system behavior is a distinct activity from modeling an optimization problem. These involve two distinct lines of expertise. In most of your courses (e.g., structures, dynamics and finance) you focused on the former.

In this book, we focus on the latter. Analysis, Design and Optimization. What is Reliability Optimization. Delivering the best reliability performance within the various constraints imposed. Without constraints such as budget, time to market, customer expectation, product functional capabilities, and product weight, you certainly could design and.

Most books on reliability theory are devoted to traditional binary models that only allow a system either to function perfectly or fail completely. The Universal Generating Function in Reliability Analysis and Optimization is the first book that gives a comprehensive description of the universal generating function technique and its.

This volume contains 28 papers by renowned international experts on the latest advances in structural reliability methods and applications, engineering risk analysis and decision making, new optimization techniques and various applications in civil engineering. Moreover, several contributions focus on the assessment and optimization of existing str.

Preface This internet publication is the second edition of Structural Reliability Methods and is a corrected and slightly revised version of the first edition published by Wiley, Chichester (ISBN The theme of this book is "Stochastic Models in Reliability and Main tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling.

Chapter 1 is devoted to "Renewal Processes," under which classical renewal theory is surveyed and computa tional methods are described. 21 hours ago  In this study, we investigated the modelling and optimization of drinking water supply system reliability in the village of Zaben, Czech Republic.

An in depth overview of the water supply network in the municipality, passport processing and accident and malfunction recording is provided based on data provided by the owner and operator of the water mains as well as the data collected by.

The main model is called RELOPT and can be used as a tool to implement: modeling reliability-based optimization design, deterioration analysis of water pipe networks, risk analysis and assessment, and decision support system. K.K. Choi is a Carver Professor of Mechanical Engineering at The University of Iowa.

He teaches in the Mechanical and Industrial Engineering Department, and is a researcher in the Center for Computer Aided Design. His research area is in mechanical system analysis, design sensitivity analysis, and reliability based design optimization.

An effective reliability programme is an essential component of every product's design, testing and efficient production. From the failure analysis of a microelectronic device to software fault tolerance and from the accelerated life testing of mechanical components to hardware verification, a common underlying philosophy of reliability applies.

Vision: modeling/simulation languages of today will become the system-programming languages of tomorrow system compiler Rich languages: concurrency, time, robustness, reliability, energy, security, Powerful analyses: model-checking, WCET analysis, schedulability, performance analysis, reliability analysis, Complex execution platforms.

Is May Reliability Basics: Reliability Allocation and Optimization using BlockSim. In last month's Reliability Basics article, we discussed some popular reliability allocation methods, including the equal, AGREE, ARINC, feasibility of objectives and repairable systems apportionment also presented some practical applications using ReliaSoft's Lambda Predict software.

Reliability: Modeling, Prediction, and Optimization (Wiley Series in Probability and Statistics) by Murthy, D. Prabhakar, Blischke, Wallace R. and a great selection of related books, art and collectibles available now at   Download this book as a print-ready *.pdf-or- Generate your own file (may be more up-to-date) As a supplement to the reference book, the BlockSim examples collection provides quick access to a variety of step-by-step examples that demonstrate how.

The models associated with the reliability estimation of power semiconductor devices are shown in Fig. Design for Reliability and Robustness (DfR2) tool platform. On the basis of lack of market-available reliability tools for power electronics, the Design for Reliability and Robustness (DfR2) tool platform is being developed.

The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization.

The GM(1,1) model’s performance is benchmarked with the Army Materiel Systems Analysis Activity (AMSAA) model, the standard within the reliability growth modeling community. For continuous and discrete (one-shot) testing, the GM(1,1) model shows itself to be superior to the AMSAA model when modeling reliability growth with small failure data.Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure.

Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at.

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