Online Program

Modeling the Reliability of Complex Systems with Multiple Data Sources: A Statistical Engineering Case Study

Keywords: Full-system data, component data, software development, SRFYDO

Estimating the reliability of complex systems with many parts and components often involves using multiple data sources, including expensive full system tests, as well as less expensive subsystem and component level tests. Using statistical methodology developed by the Statistical Sciences Group at Los Alamos National Laboratory, a process for estimating and predicting future reliability was developed. A multi-phase software tool, SRFYDO, was developed to make this process accessible and understandable to the system engineers who need to perform these analyses. In this talk, we present a short overview of the method, but focus on how the software was developed to incorporate multiple statistical tools with the goal of guiding engineers through an analysis.