A Study of the Inspection Support Tool Development Using the Neural Network

Much of the quality inspection work in the manufacturing industry is automated. However, there are many products for which inspection work cannot be automated. For example, the tip of a rotating tool (Diamond bar) is attached with diamond particles. The same thing does not exist as one diamond bar. In this study, we will develop a tool to replace manual inspection. As a basic research, we constructed a model using neural network and convolutional neural network. The model was evaluated under various conditions. As a result, the accuracy was about 75% for the neural network model and about 85% for the convolutional neural network model.