A fuzzy radial basis function neural network for predicting multiple quality characteristics of plasma arc welding

We have developed an intelligent decision support system for plasma arc welding based on a fuzzy radial basis function (RBF) neural network. This approach may solve the following problems: (1) the time-consuming learning of backpropagation neural networks, (2) the fluctuation of the values of parameters during welding, and (3) fuzzy linguistic-term judgment for welding quality. Based on the results obtained from Taguchi experiments, the developed fuzzy neural network can be trained to establish a quality prediction system for plasma arc welding. The developed system can also be applied to predict the welding quality for different designs of welding parameters, which are not trained. In addition, the system may support the plotting of a diagram of the 3D suitability region of the three remaining parameters when one parameter is fixed.