Session 4B: Failure Distributions for Parallel Dependent Identical Weibull Components

Dr. Gina Sigler, contractor with Huntington Ingalls Industries (HII), is the DoD Program Lead at the Scientific Test and Analysis Techniques (STAT) Center of Excellence (COE). She has been working at the STAT COE since 2018, where she provides rigorous test designs and best practices to programs across the DOD. Before joining the STAT COE, she worked as a faculty associate in the Statistics Department at the University of Wisconsin-Madison for three years. She earned a B.S. degree in statistics from Michigan State University, an M.S. in statistics from the University of Wisconsin-Madison, and a PhD in Applied Mathematics-Statistics from the Air Force Institute of Technology.
For a parallel system, when one component fails, the failure distribution of the remaining components will have an increased failure rate. This research takes a novel approach to finding the associated failure distribution of the full system using ordinal statistic distributions for correlated Weibull components, allowing for unknown correlations between the dependent components. A Taylor series approximation is presented for two components; system failure time distributions are also derived for two failures in a two component system, two failures in an n component system, three failures in a three component system, and k failures in an component system. Additionally, a case study is presented on aircraft turnbuckles. Simulated data is used to illustrate how the derived formulas can be used to create a maintenance plan for the second turnbuckle in the two component system.
Session Materials: dataworks.test...