Abstract: To help the platform-based products better satisfy customer’s requirements, a methodology based on quality function deployment (QFD) is proposed for optimization of scalable product platform. The main idea of this methodology is to apply the technology of QFD, establish the house of quality of each product variant, determine the optimal engineering characteristic value, perform sensitivity analysis for each engineering characteristic, establish an optimization model on the basis of obtained sensitivity indices of the engineering characteristics, and achieve the optimal platform engineering characteristic value and non-platform engineering characteristic value. The objective function of the optimization model is to maximize the average degree of customer satisfaction of all product variants in a family. The constraints of the model include the functional relationship between customer requirements and engineering characteristics and the autocorrelation function relationship among engineering characteristics. Linear function form is adopted in the model and regression method is used to estimate the parameters in the function. An example of industrial pincers is given to verify the feasibility of the proposed method, and the result of the case analysis shows that the proposed method can obtain better customer satisfaction than the traditional two-phase method.

Key words: Customer satisfaction, Product platform, Quality function deployment (QFD), cascade, heat pump drying, performance analysis, prototype testing