Predictive maintenance and improved robot efficiency are parts of the key aspects for the digital transformation in manufacturing.
Now Mitsubishi Electric is using predictive maintenance possibilities for robots that can reduce operational costs, increase asset productivity and improve process efficiency.
The cloud-based solution is based on the AI platform within IBM Watson, which enables the smart analysis of operational data to highlight maintenance requirements.
In addition, to increase the speed and efficiency of any necessary maintenance activities voice control and augmented reality have been implemented, providing opportunities for significant reductions in downtime.
Today many companies are still caught by surprise when machine failures occur. They tend to fix problems during unplanned downtime, or implement preventative maintenance based on set schedules or numbers of operational hours.
However, with predictive maintenance, production problems can be highlighted long before they result in unplanned downtime or impact on yield.
Maintenance operators can take corrective action before failure or before degraded machine performance results in faulty products being manufactured.
This latest solution from Mitsubishi Electric for predictive maintenance with robots utilises the AI platform within IBM Watson.
The platform uses predictive maintenance models, digital simulation and extrapolation of trends to provide maintenance information based on actual usage and wear characteristics. This is particularly pertinent to robots, where users don’t always appreciate that periodic maintenance is required.
Communications between the robot and the user via the cloud are two-way providing the basis for voice control of the robot.
Maintenance activities are optimised through the use of smart glasses, where the operator receives guidance on what tasks need to be performed.
The glasses can show CAD drawings of the various robot parts, superimposed over the robot itself. The glasses can also show the maintenance manual and individual instructions.