Key Engineering Characteristics Extraction Technology Based on QFD

Abstract

For many enterprises, great importance is attached to the quality control of the mechatronic product, which spends a lot of effort. Quality Function Deployment (QFD) is widely used to ensure the quality of mechatronic product and the first step is transforming customer demands to engineering characteristics. However, there are numerous engineering characteristics for a complex mechatronic product. To analyze all the characteristics will lead to unnecessary waste and inefficiency. Also, the quality is mainly ensured by the key characteristics, then these characteristics should be concentrated on. There is a lack of objective and effective technology to recognize the key engineering characteristics of the mechatronic product. This paper focuses on determining the key engineering characteristics of mechatronic product. A novel method based on the theory of QFD is therefore proposed to guarantee the quality of mechatronic product efficiently. First, it is necessary to obtain an accurate weight of customer demands. In this paper, the Kano model and vague set are combined to process customer demands for mechatronic product, which not only considers user evaluating information, but also the influencing degree to user satisfaction. Second, in order to get the objective and the precise weight of engineering characteristic, the Radial Basis Function (RBF) neural network is used to establish the relationship between customer demands and the engineering characteristics of the mechatronic product. Finally, the Pareto diagram of importance degree of engineering characteristic is constructed to obtain the key engineering characteristics of the mechatronic product. Numerical control (NC) machine tool is taken as an example and the validity and scientificity of the method are verified. The method provides a new mentality for the quality control of the mechatronic product and has important theoretical significance and broad application prospect.