Intelligent Modeling of Complex Manufacturing Processes Using Hierarchical Fuzzy Basis Function Networks

Abstract

This paper presents a generalized modeling approach to modeling of complex manufacturing processes. Fuzzy basis function networks with a novel training algorithm are used to capture the cause-effect relationships of complex manufacturing processes. The modeling scheme allows for utilization of the existing knowledge in the form of analytical models, experimental data and heuristic rules in developing a suitable model. The method is implemented for the surface grinding processes based on the hierarchical structure of fuzzy basis function networks proposed by Lee and Shin [21]. Process models for surface roughness and residual stress are developed based on the available grinding model structures with a small number of experimental data to demonstrate the concept. The accuracy of developed models is validated through independent sets of grinding experiments.