Science is helpful for engineering applications: a theoretical explanation of an empirical observation

Empirical evidence shows that when engineering design uses scientific analysis, we usually get a much better performance that for the system designed by using a trial-and-error engineering approach. In this paper, we provide a quantitative explanation for this empirical observation. 1 An Empirical Observation Observation. At a recent annual conference of the American Society of Mechanical Engineers, one of the plenary talks was given by Dr. Hai Wang from Stanford University [4]. In his talk, Dr. Wang emphasized that scientific research is important for engineering practice. His argument was that without such a research, engineers tend to concentrate on one or few parameters of the system, and experience shows that much better performance can be achieved in a scientific approach, when all the parameters of the science can changed. A similar idea was emphasized by Dr. Delbert Tesar from the University of Texas at Austin in his plenary talk at the same conference [3]. Specifically, Dr. Tesar emphasized that engineers tend to follow one – most “fashionable” – direction, i.e., modify the values of only one (or few) parameters of the systems, and this severely limits their ability to reach the most efficient solutions to practical problems. What we do in this paper. The purpose of this paper is to come up with a quantitative explanation of why the traditional trial-and-error engineering approach indeed leads to a drastic decrease in efficiency – as compared to allvariables optimization corresponding to the scientific approach.