A study of developing the parts inspection support tool using the neural network

Abstract

Recently, almost all the quality inspection work in the manufacturing industry is automated. However, there are many products for which inspection work cannot be automated. Since the tip of a rotating tool (Diamond bar) for dental care is attached with diamond particles, all parts are slightly different. In this study, we will develop a tool to replace manual inspection. As basic research, we constructed a parts model using neural network and convolutional neural network. The model was evaluated under various conditions.