Conceptual robustness in distributed concurrent engineering and design-in-modularity.

Abstract

This research addresses robustness against conceptual noise: the uncertainty posed by the indecision of members in a design team, or variations of systems in which a single component will be used. Conceptually robust solutions, solutions that would function as desired regardless of team member indecision or system variation, help achieve prompt decision making in distributed concurrent engineering and modular product designs. Dr. G. Taguchi advocates product designs that are robust against physical noise, factors not controllable by the designers, yet affecting product performance. High quality products are insensitive to these factors. This noise concept is extended here to treat both uncertainty in a design team and system variation as conceptual noise, and conceptual robustness is pursued by designers. The idea of conceptual robustness supports two formal design methodologies: distributed concurrent engineering (DCE) and design-in-modularity (DiM). In DCE, conceptual robustness enables all participating engineers to concurrently proceed with their engineering tasks, even though these are coupled to one another. In DiM, conceptual robustness provides both a formal measure of product modularity and a formal procedure for pursuing product modularity. Conceptual noise is differentiated from its physical counterpart in that conceptual noise can be eliminated, for example, by solving a more complex centralized problem. On the other hand, physical noise can only be reduced, not eliminated, by efforts such as intensive control of the manufacturing process and environment. The procedures described here exploit this difference, modeling, for instance, the value of information and the cost of time. The conceptual robustness approach provides a new theoretical basis for DCE and DiM, and new procedures for their practices. The expected advantages include quality assurance, short lead-time, modular design, and distributed system optimization. The applications of conceptual robustness in DCE and DiM were tested in industry and on problems in the literature. The DCE procedure delivered good solutions on the tested cases with the advantages of distributed problem solving. The solutions show comparable performance to those obtained through other optimization methods, and good robustness. The proposed DiM approach identified a modular design for an automotive component and proved its modularity quantitatively.