Statistical Methods for Combining Information: Stryker Family of Vehicles Reliability Case Study

• Activity Number: 545
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Rebecca Dickinson*+ and Laura June Freeman and Alyson Wilson and Bruce Simpson
• Companies: Virginia Tech and Institute for Defense Analyses and IDA and IDA
• Keywords: Reliability ; Combining Information ; Weibull Distribution ; Censored Data ; Defense

Abstract

Reliability is an essential element of system suitability in the Department of Defense. It often takes a prominent role in both the design and analysis of operational tests. However, in the current era of reducing budgets and increasing reliability requirements, it is challenging to verify reliability requirements during an initial operational test (IOT). This paper illustrates the benefits of using parametric statistical models to combine information across multiple test events. Both Frequentist and Bayesian inference techniques are employed and contrasted to illustrate different statistical methods for combining information. We apply these methods to both developmental and operational test data for the Stryker family of Vehicles. We illustrate how the conclusions of the reliability analysis would have differed if these parametric models had been used at the conclusion of the IOT.