Modern Statistical And Mathematical Methods in Reliability (Quality, Reliability and Engineering Statistics) (Quality, Reliability and Engineering Statistics)

Monograph, the 1st edition, World Scientific, London, 2005, pg.427 This volume is published on the occasion of the fourth International Conference on Mathematical Methods in Reliability (MMR 2004). A broad overview of current research activities in reliability theory and its applications is provided with coverage on reliability modeling, network and system reliability, Bayesian methods, survival analysis, degradation and maintenance modeling, and software reliability. CONTENTS: Competing risk modeling in reliability Game-theoretic and reliability methods in counter-terrorism and security Regression models for reliability given the usage accumulation history Bayesian methods for assessing system reliability - Models and computation Dynamic modeling in reliability and survival analysis End of life analysis Reliability analysis of a dynamic phased mission system - Comparison of two approaches Sensitivity analysis of accelerated life tests with competing failure modes Estimating mean cumulative functions from truncated automotive warranty data Tests for some statistical hypotheses for dependent competing risks Repair efficiency estimation in the ARI1 imperfect repair model On repairable components with continuous output Effects of uncertainties in components on the survival of complex systems with given dependencies Dynamic management of systems undergoing evolutionary acquisition Reliability analysis of renewable redundant systems with unreliable monitoring and switching Planning models for component-based software offerings under uncertain operational profiles Destructive stockpile reliability assessments - Semiparametric estimation of errors in variables with validation sample approach Flowgraph models for complex multistate system reliability Interpretation of condition monitoring data Nonproportional semiparametric regression models for censored data Binary representations of multi-state systems Distribution-free continuous Bayesian belief nets Statistical modeling and inference for component failure times under preventive maintenance and independent censoring Importance sampling for dynamic systems Leveraging remote diagnostics data for predictive maintenance From artificial intelligence to dependability - Modeling and analysis with Bayesian networks Reliability computation for usage-based testing K-mart stochastic modeling using iterated total time on test transforms This volume contains extended versions of 28 carefully selected and reviewed papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico, June 21-25, 2004, the leading conference in reliability research. The meeting serves as a forum for discussing fundamental issues on mathematical methods in reliability theory and its applications.A broad overview of current research activities in reliability theory and its applications is provided with coverage on reliability modeling, network and system reliability, Bayesian methods, survival analysis, degradation and maintenance modeling, and software reliability. The contributors are all leading experts in the field and include the plenary session speakers, Tim Bedford, Thierry Duchesne, Henry Wynn, Vicki Bier, Edsel Pena, Michael Hamada, and Todd Graves. This volume contains extended versions of 28 carefully selected and reviewed papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico, June 21-25, 2004, the leading conference in reliability research. The meeting serves as a forum for discussing fundamental issues on mathematical methods in reliability theory and its applications. A broad overview of current research activities in reliability theory and its applications is provided with coverage on reliability modeling, network and system reliability, Bayesian methods, survival anal. The competing risk problem arises quite naturally in the reliability context.