Product Design Optimization By Capturing Consumer Preference Uncertainty

As new techno logies are advanc ing and new products springing up,customer preference shows high degree of uncertainty and variety. Productdesign to take customer need into cons ideration, as the front-end of productdeve lopment, is of more importance while competition becomes fiercer. However,product design stud ies invo lving customer preference uncertainty, the dynamicupdate of customer utility and competitive products seem insuffic ient. Inresponse to the lack of literature, this paper is trying to carry out a study ofproduct design optimizatio n getting both marketing and engineering factorsinvo lved. By s ummerizing and ana lysing the previous theoritical fra meworks, aneffective quantizatio n model is developed to coordinate the goals of bothmarketing and engineering perspectives. This paper provides theory support anddesign methodology for the optimization of product design.Consumer preference is traditiona lly consideded as a deterministic processin product design optimization. Preference dyna mic and dependence suggestitse lf to be a cha llenging task. In this paper, preference dyna mic has beendescribed as a Bayesia n update process. The model of ge neralized utility isdeve loped to fac ilitate the influe nce of preference dependence. To overcome theshort of first-cho ice rule and probabilistic rule, a threshold-based choice rule ispresented.Based on the quantization model deve loped in this paper, the notebookcomp uter product design is used as the examp le and the optimizatio n results byGenetic Algorithm are obtained. The feasib ility of the product designoptimization is proved. Simulation and discussio n about key factors to theoptimization results followed. At last, the conclus ion and managia lenlightenment of product design optimization quantization model is elaborated.