Toward Autonomous Acquisition of Manufacturing Skills -The Importance of Awareness and Understanding of Embodied Cognition for Performance Improvement

Abstract

In recent years, manufacturing industries have actively introduced IoT and AI technologies into automated and robotized production processes in order to promote labor reduction and unmanned operation. At the same time, a fundamental question arises as to whether equivalent products can be realized simply by sharing manufacturing models, data, and machinery. Design data and manufacturing models used in production are spatially and temporally discrete, and manufacturing equipment cannot achieve sufficient precision or quality merely by purchase. Consequently, fine adjustment by highly skilled and experienced engineers and technicians remains indispensable. On the other hand, there are products for which the “handmade” nature itself creates high added value. Traditional crafts, for example, derive their value from the fact that materials, manufacturing methods, tools, and product designs have remained unchanged over long periods of time. From this perspective, human skills will continue to play an extremely important role in the manufacturing domain. Based on this recognition, this study develops a methodology to support the learning of human motion skills, focusing on how learners perceive bodily movements that are critical to skill improvement, how they understand the relationship between skills and physical actions, and how such understanding can be facilitated as awareness during the learning process.

Keywords: Embodied Knowledge, Tacit Skill, Manufacturing DX, AI, Skill-learning Support System, Enhancing Awareness Of Bodily Movements

DOI: 10.54941/ahfe1007350