Abstract
Within complex organizational systems such as Concurrent Engineering (CE) Product Development environments, uncertainty in information, and thus the knowledge required to make effective decisions, strongly influences the quality of the final product. Such systems are marked by high degrees of data variability making techniques such as optimization less than ideal, particularly for multiobjective problem types. Although different methods that enable designers to deal with uncertainty have been utilized, they derive from what appears to be a less than adequate representation of complex system behavior. This article presents a representation for complex systems based on the analogy of immunity where the environment of a system or “nonself” represents the set of input and outputs with the “self” of the system as the resulting “effect.” A fuzzy approach to the random perturbation of the system variables through the introduction of a global robustness index is proposed. The approach is presented in the context of decision making for tolerance control within manufacturing process design.