Collaborative Robot Case: Fujita Works Co., Ltd. TIG Welding Automation

**Reasons for Japanese Companies to Introduce Collaborative Robots in Welding Processes** **Overview:** Fujita Works Co., Ltd., a leading company in high-precision sheet metal fabrication, was considering automation to achieve TIG welding that is not dependent on the skill level of craftsmen. After repeated trials with a system integrator, they developed a UR robot solution that enables even young employees to perform high-quality TIG welding. Additionally, they automated the work of loading materials into metal press processing machines, resulting in improved work efficiency, reduced physical burden on workers, and increased satisfaction. **Challenges:** The quality of TIG welding is influenced by the technician's skill. There are concerns about a future shortage of skilled workers. **After Implementation:** By dividing the welding process into tack welding and final welding, with workers performing the tack welding and robots handling the final welding, they achieved not only stable quality but also improved work efficiency. The division of labor allowed welding tasks that previously took over three years to master to be learned in just a few months. *For details on the decisive factors for robot implementation and horizontal expansion to other processes, please refer to the linked page.* *If you would like to view a list of UR collaborative robots, please download it from the related catalog.*

Fujita Works Co., Ltd. aimed to achieve TIG welding that is not affected by the skill level of craftsmen and considered automation. After repeated trial and error with a system integrator, they developed a UR robot solution that enables even young employees to perform high-quality TIG welding. Furthermore, they automated the work of loading materials into metal press processing machines, resulting in improved work efficiency, reduced physical burden on workers, and increased satisfaction. The challenge was that the quality of TIG welding was influenced by the technician, and there were concerns about a future shortage of skilled workers. After implementation, the welding process was divided into tack welding and final welding, with workers performing the tack welding and robots handling the final welding. This not only stabilized quality but also improved work efficiency. By dividing the tasks, the welding work that previously took over three years to master could now be learned in just a few months. For more details on the decisive factors for robot implementation and horizontal expansion to other processes, please see the link.