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How Bayesian Reliability Analysis Was Developed and Implemented for Production Decisions
Bruce Baber
United States Air Force
Allan Mense
Raytheon Missile Systems
Shane Reese
Brigham Young University
Often in the development of complex discrete functioning systems the systems level testing is limited at the point significant decisions are made in the development process. One such point is typically the production decision to commit large resources to low rate initial production concurrent with the completion of developmental and operational testing. This condition introduces significant risk into the programmatic and technical management. Often these type systems are not designed from scratch, but utilize components and subsystems from previous programs that have extensive usage data in similar or identical environments. Most developments require extensive component and subsystem design verification testing and qualification testing across the environments that are expected to be encountered. A method is needed to utilize previous system development and production data and subsystem level test results combined with the systems level test data available when making reliability assessments. This paper explores Bayesian methodology to combine different types of data for evaluating system reliability for these types of systems.