The Assemblability Evaluation of Automotive Glass Windshield Mold Based on Fuzzy Neural Network

Abstract

Nowadays the production of mold seriously restricts the manufacture of products as well as the development of new products, it has become an urgent problem to be solved. The paper mainly discussed the fuzzy neural network model and learning algorithm, and utilized expert evaluating system to acquire the training and test samples. Moreover, it established the related mapping model for fuzzy neural network to evaluate the assemblability of mold, so as to improve the productivity of mold. By adopting two different fuzzy neural networks to contrast and evaluate the assemblability evaluation system of the parts of windshield mold, it was concluded that the improved fuzzy neural network model had advantage over the conventional one. Finally, the satisfactory results of assemblability evaluation system of windshield mold had been achieved by coming with examples to carry out error analysis of the assemblability evaluation system.