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RESEARCH PAPERS: Design Automation Papers

A New Approach to Probability in Engineering Design and Optimization

[+] Author and Article Information
J. N. Siddall

Department of Mechanical Engineering, McMaster University, Hamilton, Ontario, Canada

J. Mech., Trans., and Automation 106(1), 5-10 (Mar 01, 1984) (6 pages) doi:10.1115/1.3258562 History: Received October 24, 1983; Online November 19, 2009

Abstract

The anomalous position of probability and statistics in both mathematics and engineering is discussed, showing that there is little consensus on concepts and methods. For application in engineering design, probability is defined as strictly subjective in nature. It is argued that the use of classical methods of statistics to generate probability density functions by estimating parameters for assumed theoretical distributions should be used with caution, and that the use of confidence limits is not really meaningful in a design context. Preferred methods are described, and a new evolutionary technique for developing probability distributions of new random variables is proposed. Although Bayesian methods are commonly considered to be subjective, it is argued that, in the engineering sense, they are really not. A general formulation of the probabilistic optimization problem is described, including the role of subjective probability density functions.

Copyright © 1984 by ASME
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