Reliability and risk models setting reliability requirements

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.

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.

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.

3.4 Negative …