Online Program Home
My Program

Abstract Details

Activity Number: 707
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #318573 View Presentation
Title: Bayesian Signal-Response Data Nondestructive Inspection Test Planning
Author(s): Yew-Meng Koh* and William Q. Meeker
Companies: Hope College and Iowa State University
Keywords: Linear regression ; Nondestructive evaluation ; Probability of detection ; Optimum test plan ; Compromise test plan

The most common question asked of a statistician is "How large should my sample be?" In Nondestructive Evaluation applications, the most common questions asked of a statistician are "How many specimens do I need and what should be the distribution of flaw sizes?" Although some useful general guidelines exist (e.g., in MIL-HDBK-1823) it is possible to use statistical tools to provide more definitive guidelines and to allow comparison among different proposed study plans. The Bayesian methods used in this paper allow for the specification of needed planning information into the design of a study. One can assess the performance of a proposed Probability of Detection (POD) study plan by obtaining computable expressions for estimation precision. This allows for a quick and easy assessment of tradeoffs and comparison of various alternative plans. We use a signal-response dataset obtained from MIL-HDBK-1823 to illustrate the methods.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association