ABSTRACT
Product design has normally been performed by teams, each with expertise in a speci‰c discipline such as material, structural, electrical, systems. Traditionally, each team would use its members’ experience and knowledge to develop the design sequentially. Collaborative design decisions explore the use of optimization methods to solve the design problem, incorporating a number of disciplines simultaneously. It is known that the optimum of the product design is superior to the design found by optimizing each discipline sequentially due to the fact that it is enabled to exploit the interactions between the disciplines. In this chapter, a bi-level decentralized framework based on memetic algorithm (MA) is proposed for a collaborative design decision using a forearm crutch as the case. Two major decisions are considered: weight and strength. In this chapter, we introduce two design agents for each of the decisions (Wu et al., 2011). At the system level, one additional agent termed “facilitator agent” is created. Its main function is to locate the optimal solution for the system objective function that is derived from the Pareto concepts; thus, Pareto optimum for both weight and strength is obtained. It is demonstrated that the proposed model can converge to Pareto solutions.
