Current Trends in Reliability, Availability, Maintainability and Safety

Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management.

Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field.

Contains selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden Maximizes reader insights into the significance of the role of Risk Management in decision making across the various aspects of design, operation, maintenance in asset management and productivity in Industrial domains Analyzes the current industry trends in important issues concerning Risk Management and Risk Analysis and Management Systems Includes supplementary material: sn.pub/extras

Contenu
Track geometry degradation and maintenance modelling: A review.- Maintenance optimization using Multi-Attribute Utility Theory.- Context-based maintenance and repair shop suggestion for a moving vehicle.- Optimal sensor placement for efficient fault diagnosis in condition monitoring process; a case study on steam turbine monitoring.- Estimation of the reliability of rolling element bearings using a synthetic failure rate.- Malfunction in railway system and its effect on arrival delay.- On-Condition parts versus Life limited parts: A trade off in aircraft engines.- Safety and availability evaluation of railway signalling systems.- Applying multi-factorial pareto analyses in prioritizing maintenance effectiveness and efficiency improvements.- Predictive modelling for estimation of railway track degradation.