Mitsubishi Electric used EMO 2017 to demonstrate 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 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.