Reliability and Risk Models : Setting Reliability Requirements /: Setting Reliability Requirements. (2016)

• Record Type: Book
• Further Information: Note: Michael Todinov.
• Authors: Todinov, M. T
• Contents: PREFACE; ; 1. FAILURE MODES. BUILDING RELIABILITY NETWORKS; ; 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; ; 2.2 Random events in reliability and risk modelling; ; 2.3 Statistically dependent events and conditional probability in reliability and risk modelling; ; 2.4 Total probability theorem in reliability and risk modelling; ; 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; ; 3.4 Negative exponential distribution; ; 3.5 Hazard rate; ; 3.6 Mean time to failure (MTTF); ; 3.7 Gamma distribution; ; 3.8 Uncertainty associated with the mean time to failure; ; 3.9 Mean time between failures (MTBF); ; 3.10 Problems with the MTTF and MTBF reliability measures; ; 3.11 BX% life; ; 3.12 Minimum failure-free operation period (MFFOP); ; 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 models; ; 3.19 Reliability bath-tub curve; ; 4. RELIABILITY AND RISK MODELS BASED ON DISTRIBUTION MIXTURES; ; 4.1 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; ; Appendix 4.1 Derivation of the variance upper bound theorem; ; Appendix 4.2 An algorithm for determining the upper bound of the variance of properties from sampling from multiple sources; ; 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; ; 6.2 The load-strength interference model; ; 6.3 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; ; 8.2 Simulation of random variables; ; Appendix 8.1; ; 9. EVALUATING RELIABILITY AND PROBABILITY OF A FAULTY ASSEMBLY USING MONTE CARLO SIMULATION; ; 9.1 A general algorithm for determining reliability controlled by statistically independent random variables; ; 9.2 Evaluation of the reliability associated with a load-strength interference; ; 9.3 A virtual testing method for determining the probability of faulty assembly; ; 9.4 Optimal replacement to minimize the probability of a system failure; ; 10. EVALUATING THE RELIABILITY OF COMPLEX SYSTEMS AND VIRTUAL ACCELERATED LIFE TESTING USING MONTE CARLO SIMULATION; ; 10.1 Evaluating the reliability of complex systems; ; 10.2 Virtual accelerated life testing of complex systems; ; 11. GENERIC PRINCIPLES FOR REDUCING TECHNICAL RISK; ; 11.1 Preventive principles - reducing mainly the likelihood of failure; ; 11.2 Dual principles - reduce both the likelihood of failure and the magnitude of consequences; ; 11.3 Protective principles - minimise the consequences of failure; ; 12. PHYSICS OF FAILURE MODELS; ; 12.1 Fast fracture; ; 12.2 Fatigue fracture; ; 12.3 Early-life failures; ; 13. PROBABILITY OF FAILURE INITIATED BY FLAWS; ; 13.1 Distribution of the minimum fracture stress and a mathematical formulation of the weakest-link concept; ; 13.2 The stress hazard density as an alternative of the Weibull distribution; ; 13.3 General equation related to the probability of failure of a stressed component with complex shape; ; 13.4 Link between the stress hazard density and the conditional individual probability of initiating failure; ; 13.5 An algorithm for determining the probability of failure initiated by defects in components with complex shape; ; 13.6 Limiting the probability of failure and decreasing the vulnerability of designs to failure caused by flaws; ; 14. A COMPARATIVE METHOD FOR IMPROVING THE RELIABILITY OF COMPONENTS AND SYSTEMS; ; 14.1 Advantages of the comparative method to traditional methods; ; 14.2 A comparative method for improving the reliability of components whose failure is initiated by flaws; ; 14.3 A comparative method for improving system reliability; ; 14.4 A comparative method for improving the availability of flow networks; ; 15. RELIABILITY GOVERNED BY THE RELATIVE LOCATIONS OF RANDOM VARIABLES IN A FINITE DOMAIN; ; 15.1 Reliability dependent on the relative configurations of random variables; ; 15.2 A generic equation related to reliability dependent on the relative locations of a fixed number of random variables; ; 15.3 A given number of uniformly distributed random variables in a finite interval (conditional case); ; 15.4 Probability of clustering of a fixed number of uniformly distributed random events; ; 15.5 Probability of unsatisfied demand in the case of one available source and many consumers; ; 15.6 Reliability governed by the relative locations of random variables following a homogeneous Poisson process in a finite domain; ; Appendix 15.1; ; 16. RELIABILITY AND RISK DEPENDENT ON THE EXISTENCE OF MINIMUM CRITICAL DISTANCES BETWEEN THE LOCATIONS OF RANDOM VARIABLES IN A FINITE INTERVAL; ; 16.1 Problems requiring reliability measures based on minimum critical intervals (MCI) and rolling minimum failure-free operating periods (MFFOP); ; 16.2 MCI and rolling MFFOP reliability measures; ; 16.3 General equations related to random variables following a homogeneous Poisson process in a finite interval; ; 16.4 Application examples; ; 16.5 Setting reliability requirements to guarantee a rolling MFFOP followed by a downtime; ; 16.6 Setting reliability requirements to guarantee an availability target; ; 16.7 Expected fraction of the time of unsatisfied demand; ; 17. RELIABILITY ANALYSIS AND SETTING RELIABILITY REQUIREMENTS BASED ON THE COST; ; 17.1 The need for a cost-of failure-based approach; ; 17.2 Risk of failure<br /&gt
• Edition: Second edition
• Publisher Details: Chichester, West Sussex : Wiley
• Publication Date: 2016
• Extent: 1 online resource, illustrations
• Subjects: 620.00452015118; Reliability (Engineering) -- Mathematical models; Risk assessment -- Mathematics
• Languages: English
• ISBNs: 9781118873250
• Related ISBNs: 9781118873328
• Notes: Note: Includes bibliographical references and index.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.