The Computer Integrated Manufacturing Laboratory is a constituent laboratory of the Institute for Systems Research at the University of Maryland.

Updating Uncertainty Assessments: a Comparison of Statistical Approaches

• Jason Matthew Aughenbaugh, Applied Research Laboratories, The University of Texas at Austin
• Jeffrey W. Herrmann, University of Maryland, College Park

Abstract

The performance of a product that is being designed is affected by variations in material, manufacturing process, use, and environmental variables. As a consequence of uncertainties in these factors, some items A random event that occurs at most once in the lifetime of an item. The designer wants the probability of failure to be less than a given threshold. In this paper, we consider three approaches for modeling the uncertainty in whether or not the failure probability meets this threshold: a classical approach, a precise Bayesian approach, and a robust Bayesian (or imprecise probability) approach. In some scenarios, the designer may have some initial beliefs about the failure probability. The designer also has the opportunity to obtain more information about product performance (e.g. from either experiments with actual items or runs of a simulation program that provides an acceptable surrogate for actual performance). The different approaches for forming and updating the designer's beliefs about the failure probability are illustrated and compared under different assumptions of available information. The goal is to gain insight into the relative strengths and weaknesses of the approaches. Examples are presented for illustrating the conclusions.

Link to Paper

• Updating Uncertainty Assessments: a Comparison of Statistical Approaches

Copyright Notice: This paper is copyrighted and will appear in the Proceedings of IDETC/CIE 2007, ASME 2007 Design Engineering Technical Conferences & Computers and Information Engineering Conference, September 4-7, 2007, Las Vegas, Nevada. Personal use of this material is permitted. However, permission to reprint or republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists or to reuse any copyrighted component of this work in other works must be obtained from the copyright holder.

This page last updated on June 4, 2007, by Jeffrey W. Herrmann.

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