An approach to robust decision making under severe uncertainty in life cycle design

Abstract

Information-Gap Decision Theory (IGDT), an approach to robust decision making under severe uncertainty, is newly considered in the context of environmental performance affected by life cycle uncertainty. An IGDT decision strategy favours the design(s) that can endure the most estimation error while still guaranteeing no worse than some 'good enough' critical level of performance. In this paper, a simple automotive oil filter design selection example with severe uncertainty is formulated and solved using an IGDT approach. Implications of IGDT to life cycle engineering design problems are discussed, as are potential limitations that could be encountered when solving more complex problems.