The research objective of this award is to explore new paradigms for aiding product designers in decision making by combining naturalistic and mathematical decision approaches. The products and systems on which we depend are becoming increasingly complex; this is true for everything from telephones and implantable medical devices to transportation systems. However, the way in which decision making is typically carried out when designing complex products is still as much an art as it is a science. Consequently, the resulting products may not perform as well as they could. Many mathematically based decision approaches exist which could help to systematize design decision making, such as multi-criteria weighted sums and statistical methods, for example. However, designers use such methods less often in daily design work than one might hope, reporting that they are 'too busy' for such methods. Preliminary studies suggest that this is because most mathematical decision methods require entry of information which designers view as irrelevant or impractical to obtain. Statistical distributions describing likely performance of novel, untested and incompletely specified devices are an example. Further, they do not meet the designer's need for flexibility, which is essential for creative exploration of innovative solutions. This work will explore ways of better aligning mathematical decision methods with the ways in which designers naturally work.

If successful, the results of this research will lead to a better understanding of designers' natural approaches to decision making in product design, and creation of decision aids that combine the benefits of mathematical decision approaches with the flexible and creative approaches currently followed by designers. This work will help product designers to be more effective in designing complex systems, companies to be more responsive to market demand, and the next generation of designers to be trained in new and more effective ways of thinking.

Project Start
Project End
Budget Start
2009-05-15
Budget End
2014-04-30
Support Year
Fiscal Year
2009
Total Cost
$328,330
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Type
DUNS #
City
Minneapolis
State
MN
Country
United States
Zip Code
55455