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06590nam a2200697 4500 |
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150512s2015 enk ob 001 0 eng |
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|a 2015019070
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|a 921032851
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|a 9781118873199
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|a 620/.00452015118
|2 23
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|a MAIN
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|a Todinov, M. T.
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|a Reliability and risk models setting reliability requirements /
|c Michael T. Todinov.
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|a Second edition.
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|a Chichester, West Sussex, United Kingdom :
|b John Wiley and Sons, Inc.,
|c 2015.
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|a 1 online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b n
|2 rdamedia
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|a online resource
|b nc
|2 rdacarrier
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|a Wiley series in quality & reliability engineering
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|a Includes bibliographical references and index.
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|a Description based on print version record and CIP data provided by publisher.
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|a 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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|a 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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|a 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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|a 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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|a 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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|a 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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|a Reliability (Engineering)
|x Mathematical models.
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|a Risk assessment
|x Mathematics.
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|a TECHNOLOGY & ENGINEERING / Engineering (General)
|2 bisacsh
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|a TECHNOLOGY & ENGINEERING / Reference
|2 bisacsh
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|a Electronic books.
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|a Electronic books.
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776 |
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|i Print version:
|a Todinov, M. T.
|t Reliability and risk models setting reliability requirements
|b Second edition.
|d Chichester, West Sussex, United Kingdom : John Wiley and Sons, Inc., 2015
|z 9781118873328
|w (DLC) 2015016646
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830 |
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0 |
|a Wiley series in quality and reliability engineering.
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856 |
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|u https://doi.org/10.1002/9781118873199
|z Full Text via HEAL-Link
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994 |
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|a 92
|b DG1
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