Reliability Education 2011 - 2012 Training Catalog - ReliaSoft

The immensely popular G400 course sets the foundation for all subsequent seminars byintroducing and familiarizing the attendee to the fundamental concepts in reliability engineeringmathematics, from basic data analysis and modeling to advanced methods and concepts. Itbegins with an in-depth discussion of the fundamentals of Weibull and Life Data Analysis andcontinues by expanding the learned concepts to more advanced subjects. Some of the topicscovered include:• Reliability block diagram (RBD) analysis and fault tree analysis• System reliability equation and metrics• Importance analysis and reliability allocation methods• Determining optimum maintenance intervals• Reliability, availability and maintainability analysis for complex repairable systemsStatistical models for repairable systems and applications• General renewal process and recurrent event data analysis• Fielded system analysis and modelingApplying What You Will LearnG400 presents concepts and software that will help you to:````Foundations of Reliability Engineering Data Analysis and ModelingDuration: 5 daysCEUs: 3.5 CRP Credits: 5Course Prerequisites``NoneAssumes Basic Knowledge Of``Undergraduate AlgebraIntroduction to reliability engineering principles and methods``Elementary Calculus• Overview of reliability engineering theory and related mathematics, metrics andapplications``Probability and StatisticsRecommended Prior Course(s)Fundamentals of life data analysis and applications``G300• Review of relevant statistical concepts(if needed for knowledge ofprobability and statistics)• Reliability data types and censoring schemesAlternative/Similar Course(s)• Reliability metrics and their interpretation``M440• In-depth look at the Weibull distributionNext Recommended Course• Other lifetime distributions``D560 or M560• Parameter estimation methodsSoftware Used• Confidence bounds``Primary: Weibull++• Mixed Weibull distribution``Supplemental:• Competing failure modes analysisALTA, BlockSim, RGA• Degradation data analysis• Warranty data analysis• Model and data set comparisons• Reliability test design• Reliability demonstration• Stress-strength analysis• Case studies and hands-on practice using Weibull++Advanced life data modeling and applications• Combining life-stress relationships with lifetime distributions• Quantitative accelerated life testing (ALT) data analysis with life-stress models for one or multiple stressesSystem analysis, modeling and applicationsUnderstand how life data analysis methodologies can be applied when you need to understand and communicate how aproduct will perform over time, such as:• Setting meaningful reliability targets, demonstrating whether an item meets the specification and/or effectivelycommunicating performance estimates to management.• Identifying whether an item will experience infant mortality and/or wearout and making predictions aboutperformance during the useful life (or warranty) period.• Evaluating suppliers and/or comparing designs based on reliability.Become familiar with the applications of other essential reliability data analysis methods, such as ALT, RBDs and RGA.6