DRIVEN

Machine efficiency losses are one of the main and most common concerns in industrial processes. With that in mind, DRIVEN proposes to analyze, simulate and optimize the entire operation of product movements between the parts warehouse, the packaging process in an automotive component factory.
Even models, analytics and optimizations exist, DRIVEN will develop and use two new technologies. Digital Twin for machine performance analysis, based on artificial vision and image recognition and Risk of Failure Forecasting, monitoring the machine performance in real time through the digital twin using Convolutional Neural Network.
To that, DRIVEN will make intensive use of the DIGITbrain platform, from the edge layer to the user interfaces in a web-based environment. The experiment will optimize production processes by achieving a significant increase in the OEE, and also fostering the democratisation of technologies, opening the way to new business models based on data exploitation.

Beneficiaries of DRIVEN Experiment