Robust Analysis of Degradation Measures Using Quantile Regression

• Activity Number: 470
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Jonathan Lane*+ and Stephen V. Crowder
• Companies: Sandia National Laboratories and Sandia National Laboratories
• Keywords: Degradation Measure ; Quantile Regression ; Bootstrap ; Test Plan

Abstract

With short production development times, there is an increased need to demonstrate product reliability relatively quickly with minimal testing. In such cases there may be few if any observed failures. Thus it may be difficult to assess reliability using the traditional reliability test plans that measure only time (or cycles) to failure. For many components, degradation measures will contain important information about performance and reliability. These measures can be used to design a minimal test plan, in terms of number of units placed on test and duration of the test, necessary to demonstrate a reliability goal. Generally, the assumption is made that the error associated with a degradation measure follows a known distribution, usually normal, although in practice cases may arise where that assumption is not valid. In this work, we examine such degradation measures and present methods using quantile regression to demonstrate reliability and to develop reliability test plans for the future production of components with this form of degradation.