EMO 2017 saw Mitsubishi demonstrating innovative 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 down-time.
Many companies today are still caught by surprise when machine failures occur. They tend to fix problems during unplanned down-time, 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.
Voice commands for Mitsubishi Electric robots
To increase the efficiency of maintenance operations, the demonstration at EMO 2017 highlighted the implementation of hands-free operation of the robot. Communications between the robot and the user via the cloud are two-way providing the basis for voice control of the robot. The demonstration also shows how additional support for maintenance activities can be provided, through a series of voice commands.
Augmented reality provides additional support for maintenance
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.
As well as highlighting predictive maintenance, the demonstration on the Mitsubishi Electric stand at EMO 2017 showed how integrated safety can help manufacturers to optimise floor space, boost productivity and reduce down-time while maintaining a safe environment for operators.
Predictive maintenance and improved robot efficiency are parts of the key aspects for the digital transformation in manufacturing, and were some of the important themes of the Mitsubishi Electric stand at EMO 2017.