Radial Basis Function Neural Network method of determining functional relationships for Quality Function Deployment

Quality function deployment (QFD) is a systematic approach that captures customer requirements and translates them, through house of quality (HOQ), into engineering characteristics of product. As the functional relationships between customer requirements and engineering characteristics in QFD are uncertain, unclear and fuzzy, radial basis function (RBF) to determine the functional relationships for QFD is presented, and a QFD functional relationships model based on RBF is proposed. According to RBF neural network can realize the nonlinear mapping space from the input space to the output, and can obtain the optimal relationships pattern of the input and output, the customer requirements and engineering characteristics in QFD constituted the input and output of the RBF neural network respectively, the optimal relationships are constructed through the neural network training. A case study of natural lighting products development is provided to illustrate the application of the presented method.