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Enabling the Smart Factory with new MELIPC edge computing

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Companies with a requirement to combine factory floor operational technology (OT) and IT systems now have a new option from Mitsubishi Electric. The MELIPC edge computing solution offers optimisations such as predictive maintenance or quality control with real-time data analysis
and early feedback to the operator.

Manufacturing quality and productivity gains can be made in industries such as automotive, food & beverage and life science using the MELIPC solution. The real-time process software provides local diagnostics, predictive feedback and visualisation for shop-floor analytics.

Analysis algorithms for predictive maintenance and quality control are already on-board of the MELIPC Series. In continuous production applications it can improve processes as well as adapting to variables. Efficiency is improved by generating a live predictive model, which can be updated and refined based on new demands from the process. A packaging machine in a food & beverage application for instance can predict issues and avoid mistakes, thereby improving quality.

The MELIPC solution can recognise anomalies in machine status in real time by making use of artificial intelligence (AI). In an automotive paint shop for example, it can be used to prevent downtime. Detailed status information is reported back to the automation level so that machine operators can make
pro-active early adjustment or maintenance interventions to maintain efficiency and increase availability.

Processing data at the physical edge of operations can also improve data security and process integrity. In a life science application, the MELIPC solution can be used to store and analyse sensitive information on OT level, instead of it being sent up into the cloud. This also provides much faster realtime-diagnosis while reducing IT infrastructure cost and requirements. The new MELIPC solution complements Mitsubishi Electric’s existing edge computing portfolio such as the MAPS SCADA, data logging and Controller modules.

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