The objective of this collaborative research project is to measure the information content of different artifacts used in early design no matter how the design is described, and also to study the growth of information, or reduction of uncertainty, in the early stages of engineering design. Information of various types is produced and used in design, and each may be expressed in different forms, such as pictures, text, symbols, or animation. A general design representation is being developed to translate any type of design information into a neutral form. Second, metrics are being created to measure the information content of artifacts based on this neutral representation, along with tools to quantify the information content of designs. Models developed on an earlier project will be used to validate the information metrics by experimentally measuring how information within different designs, as measured by the metrics, can reduce design uncertainty.
If successful, this research will transform the methods for control and evaluation of engineering design projects. With information measurable in the context of decisions, computer tools and formal methods could be built to measure the progress of design projects in terms of the information used and decisions made, rather than the more indirect metrics used today, such as time elapsed or money spent. This research will stimulate new research into the understanding and measurement of the "state of knowledge" of a design team. By having a way to measure knowledge state, it could be possible to quantify the designer's knowledge gain throughout a design project, which could lead to new tools and methods for evaluating a design team's capability in retaining and reusing knowledge between projects, and for objectively assessing the learning curves of student design teams. The findings of this research will be integrated into design-related courses at both Texas State University and Oregon State University in order to improve students' appreciation for "learning by doing" and give them a better feel for the complexity of decision-making in engineering design.
