Propagation of Epistemic Uncertainty for Design Reuse

There are two sorts of uncertainty inherent in engineering design, the random and the epistemic. Random, or stochastic, uncertainty deals with the randomness or predictability of an event. It is well understood, easily modeled using classical probability, and ideal for such uncertainties as variations in manufacturing processes or material properties. Epistemic uncertainty deals with our lack of knowledge, our lack of information, and our own and others' subjectivity concerning design parameters. Epistemic uncertainty plays a particularly important role in the early stages of engineering design, when a lack of information about nominal values of parameters is much more important than potential variations in those parameters. Design reuse, or the design of product platforms, is an example in which epistemic uncertainty can play a crucial role in early design. While there are many methods to incorporate random uncertainty in a design process, there are fewer that consider epistemic uncertainty. There are fewer still that attempt to incorporate both sorts of uncertainty, and those that do usually attempt to model both sorts using the same uncertainty model. Two methods, a range method and a fuzzy sets approach, are proposed to achieve designs that are robust to both epistemic uncertainty and random uncertainty. Both methods incorporate preference aggregation methods to achieve gore appropriate trade-offs between performance and variability when considering both sorts of uncertainty. The proposed models for epistemic uncertainty are combined with existing models for stochastic uncertainty in a two-step process.