Saxony: Dulig sees great potential in Saxony as a land of robots

Saxony's government is dedicating a separate theme day to important economic issues.

Saxony: Dulig sees great potential in Saxony as a land of robots

Saxony's government is dedicating a separate theme day to important economic issues. After hydrogen and company succession, it is now the turn of robots and artificial intelligence. As a land of inventors, the Free State believes it is in the front row.

Dresden (dpa / sn) - According to Economics Minister Martin Dulig (SPD), Saxony has what it takes to become a leading location for robot technology in Europe. Robotics and artificial intelligence (AI) are innovation drivers for the economy, he said on Tuesday in Dresden. "In this context, cross-industry cooperation is becoming increasingly important."

In the afternoon, as part of a theme day organized by his ministry, Dulig found out more about the use of robots at the National Center for Tumor Diseases at Dresden University Hospital and from a stonemason. The minister explained that they would also offer new opportunities to increase productivity and a healthy, ergonomic way of working, especially in the skilled trades.

"With outstanding competencies in the fields of microelectronics, mechanical engineering and software, Saxony sets its own course in robot technologies. University spin-offs and start-ups contribute to this, as do established automation companies," stressed Dulig. One is broadly positioned in robotics and AI - from development to application, in hardware and software, from individual items to industrial production. "This diversity is a location advantage."

According to the ministry, around 35,000 employees in Saxony work with robotics. The robot density in Germany - the number of industrial robots per 10,000 employees - rose to a new record of 371 units in 2020. With a total of 230,600 units, Germany has a 38 percent share of the total number of operative industrial robots in Europe. The robot density is an important indicator for determining the degree of automation in national economies.