Epson Develops System for Simultaneously Managing Multiple Robots

Epson has developed an Epson Robot Management System to simultaneously manage multiple Epson robots on a manufacturing line using networked PCs and tablets. This system enables manufacturers that use Epson robots to increase the efficiency of factory administration and robot maintenance.

The Epson Robot Management System uses PCs and tablets connected to an intranet network to centrally monitor a factory’s industrial robots, acquire robot status backups, update firmware, and simultaneously update operating programs.

In the past, Epson industrial robot users had to monitor robots individually and separately enter program settings and so forth for each. Taking regular backups and performing maintenance in factories with multiple robots could be complicated and time-consuming, and it took time and trouble to restore operations when issues occurred. The Epson Robot Management System increases the efficiency of factory operations by solving these issues.

Until now, Epson was largely focused on helping to create an environment that enables customers to more easily realise complex applications, such as by helping to increase the efficiency of equipment design using simulator functions and by reducing equipment setup times with Epson robot integrated force sensors and image processing sensors. Going forward, Epson will develop and provide solutions that enable smarter manufacturing and support factory administration. In addition to the Epson Robot Management System, these solutions will include systems that are compliant with the OPC-UA (an industry standard communication protocol for IoT) and that leverage AI to increase the efficiency of robot operations and predict failures.

Epson recently exhibited at the International Robot Exhibition where among the reference exhibits on the Epson booth were ones that demonstrated:
• Use of a robot monitoring system to display the status of robots operating in the booth
• Increasing efficiency with AI-based machine learning of applications that use force sensors
• Concept for OPC-UA protocol support