Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 06, 2021 - June 08, 2021
In recent years, the shortage of successors has become a serious problem in the manufacturing industry due to the declining birthrate and the aging of skilled workers. To tackle this problem, a new education and training systems utilizing ICT technology that improves the efficiency of education is required. In this paper, we focused on the education of welding work and proposed a new work evaluation system that visualizes arc welding operations and evaluates the similarity with skilled workers. The proposed method can extract low-dimensional feature vectors from measured welding torch postures and current and voltage values, and accurately classifies them into multiple clusters acquired by unsupervised learning. The experimental results showed that the proposed system achieved high classification performance and suggested the possibility of using them for training in welding operations.
