Entropic Method for Sequencing Discrete Design Decisions

Abstract

Early stages of engineering design processes are characterized by high levels of uncertainty due to incomplete knowledge. As the design progresses, additional information is externally added or internally generated within the design process. As a result, the design solution becomes increasingly well-defined and the uncertainty of the problem reduces, diminishing to zero at the end of the process when the design is fully defined. In this research a measure of uncertainty is proposed for a class of engineering design problems called discrete design problems. Previously, three components of complexity in engineering design, namely, size, coupling and solvability, were identified. In this research uncertainty is measured in terms of the number of design variables (size) and the dependency between the variables (coupling). The solvability of each variable is assumed to be uniform for the sake of simplicity. The dependency between two variables is measured as the effect of a decision made on one variable on the solution options available to the other variable. A measure of uncertainty is developed based on this premise, and applied to an example problem to monitor uncertainty reduction through the design process. Results are used to identify and compare three task-sequencing strategies in engineering design.