Considering the Info-Gap Approach to Robust Decisions Under Severe Uncertainty in the Context of Environmentally Benign Design

Abstract

Information-Gap Decision Theory (IGDT), an approach to robust decision making under severe uncertainty, is considered in the context of a simple life cycle engineering example. IGDT offers a path to a decision in the class of problems where only a nominal estimate is available for some uncertain life cycle variable that affects performance, and where there is some unknown amount of discrepancy between that estimate and the variable's actual value. Instead of seeking maximized performance, the decision rule inherent to IGDT prefers designs with maximum immunity (info-gap robustness) to the size that the unknown discrepancy could take. This robustness aspiration is subject to a constraint of achieving better than some minimal requirement for performance. In this paper, an automotive oil filter selection design example, which involves several types of severe uncertainty, is formulated and solved using an IDGT approach. Particular attention is paid to the complexities of assessing preference for robustness to multiple severe uncertainties simultaneously. The strengths and limitations of the approach are discussed mainly in the context of environmentally benign design and manufacture.