Predictive maintenance reduces cost the smart way

Mitsubishi Electric and its e-F@ctory Alliance partner Lenord + Bauer have developed an advanced condition monitoring system for machine tools. It utilises smart encoders and a direct communication interface within Mitsubishi Electric machine controllers, such as CNCs, for accurate status information that is easy to access.

Operating hours are recorded and monitored along with temperature, speed and position by the Lenord + Bauer MiniCODER range. These parameters are then used to help schedule maintenance activities by providing an early warning message when component servicing or replacement are required. The ferromagnetic measuring gear and scanning unit can record speeds of up to 100,000 revolutions per minute, making the system ideal for feedback on machine tool spindles and positioning systems.

The second solution on the stand uses AI to increase the effectiveness of predictive maintenance. The cloud-based solution using the AI platform within IBM Watson analyses operational data and can optimise maintenance regimes based on actual usage and wear characteristics. It can be applied to robots and other equipment such as machine tools.

Both smart solutions demonstrate how predictive maintenance for machine tools and robots can reduce operational costs, increase asset productivity and improve process efficiency.