The industry of the future, also known as Industry 5.0, aims to modernize production tools, digitize workshops, and cultivate the invaluable human capital within the company. Industry 5.0 can't be done without fostering a workforce that is not only technologically adept but also has enhanced skills and knowledge. Specifically, collaborative robotics plays a key role in automating strenuous or repetitive tasks, enabling human cognitive functions to contribute to quality and innovation. In manual manufacturing, however, some of these tasks remain challenging to automate without sacrificing quality. In certain situations, these tasks require operators to dynamically organize their mental, perceptual, and gestural activities. In other words, skills that are not yet adequately explained and digitally modeled to allow a machine in an industrial context to reproduce them, even in an approximate manner. Some tasks in welding serve as a perfect example. Drawing from the knowledge of cognitive and developmental psychology, professional didactics, and collaborative robotics research, our work aims to find a way to digitally model manual manufacturing skills to enhance the automation of tasks that are still challenging to robotize. Using welding as an example, we seek to develop, test, and deploy a methodology transferable to other domains. The purpose of this article is to present the experimental setup used to achieve these objectives.

翻译：未来工业，即工业5.0，旨在推动生产工具现代化、车间数字化，并培育企业内部宝贵的人力资本。工业5.0的实现离不开一支既精通技术又具备增强技能与知识的劳动力队伍。具体而言，协作机器人在自动化繁重或重复性任务中发挥关键作用，使人类认知功能能够专注于质量提升与创新。然而，在手动制造中，部分任务仍难以在保证质量的前提下实现自动化。某些情况下，这些任务要求操作员动态组织其心理、感知和肢体活动——换言之，这些技能尚未得到充分解释和数字化建模，使得工业环境中的机器即使以近似方式也无法复现。焊接领域的某些任务便是典型例证。结合认知与发展心理学、专业教学法及协作机器人研究的成果，本研究旨在探索一种数字化建模手动制造技能的方法，以提升当前机器人化困难任务的自动化水平。以焊接为例，我们致力于开发、测试并推广一种可迁移至其他领域的方法论。本文旨在介绍为实现上述目标所设计的实验方案。