Quality function deployment as a tool for including customer preferences in optimising vehicle dynamic behaviour

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Quality function deployment as a tool for including customer preferences in optimising vehicle dynamic behaviour

Haghiac, Horia A. / Haque, Imtiaz

Expert simulation can solve problems that are beyond the power of even the most insightful designers. However, it also suggests the potential for equipping designers with tools that enhance their insight. This paper proposes a combined application of the Quality Function Deployment (QFD) design technique and a Genetic Algorithm-based (GA) optimisation method to a multi-criteria optimisation design problem to reduce the dimensionality of the problem. QFD can be difficult to use because big problems produce big Houses of Quality, which leads to difficulties in interpretation. However, the goal here is to try to show a different aspect of the method, i.e. introducing such a study into an optimisation process can reduce the scale of the problems in such a way that what the customer really wants is not neglected. In the case presented here, 24 design parameters and 22 performance indices were reduced to 14 and 18 parameters respectively. The results are obtained faster and they are better numerically and focus on what the customer really wants. In was shown in this study that QFD could be applied before or after the optimisation process. Applying the design study at the beginning reduces the amount of the input and output parameters and the CPU time for the GA optimisation process is 25% less (Haghiac, 2003). This leads to a shorter and more focused, from the point of the customer, optimisation process. In the case when computational resources are big enough and the design team doesnt have a very strict time frame for solving a particular problem, the QFD study can be applied after the optimisation process. Usually an optimisation process reveals a Pareto set of solutions. QFD helps designers minimise the number of the solutions and finally choose the one which better serves the customer's demands. As customer satisfaction, timeliness and correctness become more and more crucial to success in the international marketplace, QFD will be more and more widely applied in the product-realisation system. This approach can be applied to a variety of multi-criteria optimisation-design problems where a customer's preference can be integrated into the design process.