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BL
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| Record Number
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641170
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| Doc. No
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dltt
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| Main Entry
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Todinov, M. T.
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| Title & Author
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Reliability and risk models setting reliability requirements /\ Michael T. Todinov
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| Edition Statement
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Second edition
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Second edition
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| Series Statement
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Wiley series in quality & reliability engineering
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| Page. NO
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1 online resource.
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| ISBN
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9781118873250 (epub)
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: 1118873254 (epub)
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: 9781118873311 (pdf)
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: 1118873319 (pdf)
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9781118873328 (cloth)
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: 9781118873199
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: 111887319X
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1118873327 (cloth)
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| Bibliographies/Indexes
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Includes bibliographical references and index
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| Contents
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Title Page; Table of Contents; Series Preface; Preface; 1 Failure Modes; 1.1 Failure Modes; 1.2 Series and Parallel Arrangement of the Components in a Reliability Network; 1.3 Building Reliability Networks: Difference between a Physical and Logical Arrangement; 1.4 Complex Reliability Networks Which Cannot Be Presented as a Combination of Series and Parallel Arrangements; 1.5 Drawbacks of the Traditional Representation of the Reliability Block Diagrams; 2 Basic Concepts; 2.1 Reliability (Survival) Function, Cumulative Distribution and Probability Density Function of the Times to Failure
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2.2 Random Events in Reliability and Risk Modelling2.3 Statistically Dependent Events and Conditional Probability in Reliability and Risk Modelling; 2.4 Total Probability Theorem in Reliability and Risk Modelling. Reliability of Systems with Complex Reliability Networks; 2.5 Reliability and Risk Modelling Using Bayesian Transform and Bayesian Updating; 3 Common Reliability and Risk Models and Their Applications; 3.1 General Framework for Reliability and Risk Analysis Based on Controlling Random Variables; 3.2 Binomial Model; 3.3 Homogeneous Poisson Process and Poisson Distribution
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3.4 Negative Exponential Distribution3.5 Hazard Rate; 3.6 Mean Time to Failure; 3.7 Gamma Distribution; 3.8 Uncertainty Associated with the MTTF; 3.9 Mean Time between Failures; 3.10 Problems with the MTTF and MTBF Reliability Measures; 3.11 BX% Life; 3.12 Minimum Failure-Free Operation Period; 3.13 Availability; 3.14 Uniform Distribution Model; 3.15 Normal (Gaussian) Distribution Model; 3.16 Log-Normal Distribution Model; 3.17 Weibull Distribution Model of the Time to Failure; 3.18 Extreme Value Distribution Model; 3.19 Reliability Bathtub Curve
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4 Reliability and Risk Models Based on Distribution Mixtures4.1 Distribution of a Property from Multiple Sources; 4.2 Variance of a Property from Multiple Sources; 4.3 Variance Upper Bound Theorem; 4.4 Applications of the Variance Upper Bound Theorem; 5 Building Reliability and Risk Models; 5.1 General Rules for Reliability Data Analysis; 5.2 Probability Plotting; 5.3 Estimating Model Parameters Using the Method of Maximum Likelihood; 5.4 Estimating the Parameters of a Three-Parameter Power Law; 6 Load-Strength (Demand-Capacity) Models; 6.1 A General Reliability Model
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6.2 The Load-Strength Interference Model6.3 Load-Strength (Demand-Capacity) Integrals; 6.4 Evaluating the Load-Strength Integral Using Numerical Methods; 6.5 Normally Distributed and Statistically Independent Load and Strength; 6.6 Reliability and Risk Analysis Based on the Load-Strength Interference Approach; 7 Overstress Reliability Integral and Damage Factorisation Law; 7.1 Reliability Associated with Overstress Failure Mechanisms; 7.2 Damage Factorisation Law; 8 Solving Reliability and Risk Models Using a Monte Carlo Simulation; 8.1 Monte Carlo Simulation Algorithms
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| Abstract
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A comprehensively updated and reorganized new edition. The updates include comparative methods for improving reliability; methods for optimal allocation of limited resources to achieve a maximum risk reduction; methods for improving reliability at no extra cost and building reliability networks for engineering systems. Includes: -A unique set of 46 generic principles for reducing technical risk -Monte Carlo simulation algorithms for improving reliability and reducing risk -Methods for setting reliability requirements based on the cost of failure -New reliability measures based on a minimal separation of random events on a time interval -Overstress reliability integral for determining the time to failure caused by overstress failure modes -A powerful equation for determining the probability of failure controlled by defects in loaded components with complex shape -Comparative methods for improving reliability which do not require reliability data -Optimal allocation of limited resources to achieve a maximum risk reduction -Improving system reliability based solely on a permutation of interchangeable components
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| Subject
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Reliability (Engineering)-- Mathematical models.
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| Subject
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Risk assessment-- Mathematics.
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| Dewey Classification
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620/.00452015118
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| LC Classification
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TA169
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| Added Entry
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Ohio Library and Information Network.
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