Function-Costing Applied to Brushless D.C. Permanent Magnet Motors

Abstract

Abstract Function-costing is a cost-estimation hypothesis that helps designers estimate costs from a product’s specifications. It is surmised, that for a class of products, the relationship between cost and the primary function can be captured in a mathematical relation. It proceeds on the basis that in a free market, the lowest cost of a product will emerge over time and this cost can be roughly approximated from the product’s primary performance function. In this paper, we validate the function-costing hypothesis for Brushless D.C. permanent magnet motors (BDCPMMs). The principal function of these motors is to provide torque and the peak torque is chosen as the primary performance function. From the cost-peak torque data of a family of eight BDCPMMs produced by a motor manufacturer, we obtain a regression-based cost-estimation relation based on the function-costing hypothesis. The manufacturing processes involved in the BDCPMM construction are studied. A detailed cost-estimation function — in terms of the BDCPMM design variables — is developed using the principle of similarity and the cost data from the eight motors. The costs of constructing a motor for different peak torques is then obtained from a nonlinear discrete optimization formulation (minimum cost objective), which is solved using a genetic algorithm. These costs compare well with the costs predicted by function-costing and validate the hypothesis for BDCPMMs. Finally, we investigate potential applications of function-costing to BDCPMM redesign.