Engineering parameter selection for design optimization during preliminary design

Abstract

Matrix methods such as the House of Quality are useful as a first step in organizing the information relating product attributes to engineering parameters. However, they frequently result in a large number of elements, making it very difficult to focus attention on elements that bring maximum benefits. This paper presents a method for reducing a large set of engineering parameters to a more efficient subset. The method proposed first quantifies the values in the relationship matrix using indifference statements. A set of rules is then applied to the relationship matrix to redefine, separate, combine and eliminate some engineering parameters and to account for the controllability and quantifiability of engineering parameters. These adjusted values are then used in an integer programming formulation to identify the subset of engineering parameters that offers the greatest potential for cost control. This is where product development, experimental and optimization efforts should be focused. An example of a new air pollution control system illustrates the method. The most efficient set of engineering parameters are identified, which are then defined as decision variables in a cost-minimization model. The optimal design identified by the method significantly reduces cost, compared with both the original product configuration and with the configuration resulting from a reasonable (but ad hoc) attempt at reducing the number of engineering parameters in the original House of Quality.

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