Reliability & P-CAM - In-depth Reliability and data analysis

The participant makes the data talk to provide an overview to target assets of concern. He acquires the knowledge and tools for analyzing dependability (RAMS) to optimize strategies based on field data driven decisions.He will go beyond the simple theory, to learn the language of assets, interpret their messages and continually evaluate the strategies put in place for optimal and sustainable performance ;to understand the link between reliability theory, associated algorithms and the field,to adapt theories to their own operational context using the P-CAM process,to develop benchmarks to facilitate decision-making for asset management,to continuously improve the strategies in place, monitoring the associated results,and most importantly ; to avoid drowning in trivial details.This training is for people involved or having an interest in the management of physical assets, operational excellence or maintenance engineering, and looking for a new perspective.ObjectivesOptimize asset management strategies using the concepts of dependability (Reliability, Availability, Maintainability and Safety – RAMS) and the estimation of reliability in operationDefine dependability (RAMS) and associated conceptsDefine reliability, bathtub curve and associated modelsEstimate reliability from operating dataOptimize reliability using redundanciesTargeted participantsEngineers, analysts, reliability experts, managers, technicians, planners, maintainers, operators and professionals involved in optimizing the dependability of assets.MethodologyThrough presentations and analytical exercises, the participant becomes familiar with the concepts of dependability, so that he can use them in a process of continuous improvement.Presentations (40%), analysis exercises (60%)TRAINING OUTLINE / SYLLABUSDependability (15%)ReliabilityAvailabilityMaintainabilitySafetyReliability (20%)Laws of reliabilityBathtub curve conceptsExponential modelWeibull modelParts replacement timeMeasuring Reliability (45%)Complete dataTruncated/censored dataConfidence intervalGraphic methodsModels validationImprove through redundancy (20%)Serial systemsParallel systemsMajority systemsPending systemsMixed systems