Ph.D. Proposal Presentation by
Jason Aughenbaugh

Wednesday, August 31, 2005

(Dr. Chris Paredis, Chair)

"Managing Uncertainty in Engineering Design Using Imprecise Probabilities and Principles of Information Economics"

__Abstract__

The engineering design community recognizes that an essential part of the
design process is decision-making. Each decision consists of two main phases—problem
formulation and problem solution. Existing literature focuses on problem *solution * using
precisely known probabilities. Problem *formulation * has received
considerably less attention. The objective of this thesis is to investigate
methods for managing uncertainty during the formulation phase of engineering
design decisions, focusing on situations in which probabilities are not
precisely known. The existence of such situations has been recognized in
the decision theory community but has not been addressed substantially in
engineering design problems. The thesis seeks to identify the fundamental
characteristics of uncertainty in the context of engineering design, and
hypothesizes that subjective, *imprecise probabilities * are more
general and appropriate than currently used representations. Many methods
of uncertainty representation are rigorous and internally consistent, but
the applicability of the starting axioms must be evaluated. Further, the
thesis will develop a method for comparing the *practical value * of
alternative problem formulations and uncertainty representations, taking
into account not only the mathematical expressiveness of the formalism,
but also the cost of the computations. This is an *information management * problem
to which principles of *information economics * will be applied for
determining an appropriate cost-benefit tradeoff. Finally, the thesis will
evaluate decision-policies for problems with imprecisely known probabilities.