The development of Human-Robotic cooperation (HRC) in manufacturing is at an early stage. Collaborative robot (cobot) design allows them to work alongside people in a production cell. It is no longer necessary to install them behind protective safety barriers. Moreover, free from these restriction, collaborative robots are deployable anywhere in the production environment.
Importantly, the accuracy of collaborative robots allows their use in in precision applications. The performance of Mitsubishi Electric cobots mirror that of their high-performance cousins. This means a repeat accuracy of ±0.02 mm, despite the inclusion of sensitive force/torque sensors. Load capacity of the shown robot model is between 5 and 6 kg and reach is between 800 and 1000 mm.
As well as performance, Mitsubishi Electric has also addressed ease of use. It uses unique and innovative control and programming options, like touch-screen operator terminals. These plugs into the robot, provides an intuitive interface to ‘teach’ the robot its task. Thus, requiring no special programming expertise. The teach functionality includes a ‘direct control’ mode allowing the operator to change the robot position by hand using controlled force. Once the set-up is complete, the operator terminal removes to give the robot full freedom of movement.
New concept in robotics for predictive maintenance
As the use of robots increases, their reliability becomes increasingly important. Like most precision equipment, robots need appropriate maintenance to avoid unplanned downtime. Predictive maintenance ensures early identification of production problems.
In the event of a problem, detection occurs long before it causes unplanned downtime. Early corrective action reduces degraded machine performance results impacting on yield. Furthermore, early operator action protects the cobot from expensive long-term damage.
To identify deviations from normal operating parameters Mitsubishi predictive maintenance uses artificial intelligence. platform within IBM Watson. Watson is a question answering computer system for answering questions posed in natural language.
It uses predictive maintenance models, digital simulation and extrapolation of trends. They provide maintenance information. based on actual usage and wear characteristics. This is particularly pertinent, as robot users don’t always appreciate the need for periodic maintenance.
Further improving speed and efficiency of maintenance, are voice control and augmented reality.
Voice commands for Mitsubishi Electric Robots
Voice control of the robot by the operator is two-way and delivered through the cloud. Furthermore, the concept includes supporting maintenance activities using a series of voice commands. The robots plug into a robot CPUs mounted in Mitsubishi’s iQR automation platform. This provides users full integration to Industry 4.0. manufacturing
Augmented reality support
Finally, augmented reality provides extra support for maintenance using smart glasses. These enable the operator to receive guidance on what tasks that need performing. The glasses can show CAD drawings of the various robot parts, superimposed over the robot itself. Further, the glasses can show the maintenance manual, individual instructions and list spare parts.
Repetitive tasks using collaborative robots offer manufacturers a competitive option for improving productivity. They are accurate and reliable, and their use of augmented intelligence is developing their capability. The robots plug directly into a robot CPU mounted in Mitsubishi’s iQR automation platform for full integration to Industry 4.0. manufacturing.
iQ-R control platform offers fast processing, network and module synchronization, and multi-discipline control. Significantly, its advanced design provides users with industries leading superior machine performance and productivity. It offers a multitude of CPU and I/O module options, hence providing a flexible solution for a wide variety of applications.
BPX offers a wide range of ancilliary tools and integrators to helps customer integration of collaborative robots
