A study on the sample extraction for a quality inspection tool and operator training
AKAISHI Riku, Harumi HARAGUCHI · The Proceedings of Manufacturing Systems Division Conference · 2021
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 train the inspection work and to replace manual inspection. As basic research, we checked the training effect by training tool and constructed a parts model using neural network and convolutional neural network. This model was evaluated using the training result.