2024 年 28 巻 4 号 p. 137-140
While the automation and intellectualization of factories are advancing due to the promotion of Digital Transformation (DX), there are still many processes and tasks that require craftsmen. The efficiency improvement of skill transfer is very important, and a system that quickly develops beginners into skilled workers is necessary. Therefore, it is necessary to have a technique for numerical measurement and visualization of proficiency. Although images are generally used for the recognition of work action, we have shown that action recognition and task segmentation can be achieved to a high degree of accuracy using only information from microphones and inertial measurement devices that are worn by workers. On this basis, a method for automatically visualizing the proficiency of workers in assembly work using inertia and sound sensors was examined.