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.
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March 1984
This article was originally published in
Journal of Mechanisms, Transmissions, and Automation in Design
Research Papers
A New Approach to Probability in Engineering Design and Optimization
J. N. Siddall
J. N. Siddall
Department of Mechanical Engineering, McMaster University, Hamilton, Ontario, Canada
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J. N. Siddall
Department of Mechanical Engineering, McMaster University, Hamilton, Ontario, Canada
J. Mech., Trans., and Automation. Mar 1984, 106(1): 5-10 (6 pages)
Published Online: March 1, 1984
Article history
Received:
October 24, 1983
Online:
November 19, 2009
Citation
Siddall, J. N. (March 1, 1984). "A New Approach to Probability in Engineering Design and Optimization." ASME. J. Mech., Trans., and Automation. March 1984; 106(1): 5–10. https://doi.org/10.1115/1.3258562
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