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Digital Twin

Digital Model based on the concept of a digital production platform consisting of common systems, functional systems and specific systems.
Enables the development and test, in a virtual enviroment, of several approaches for a specific production systems with the goal to find the best and flexible solution to the current and future manufacturing challenges: High Throughput and High Variability


Machine Learning ecosystem composed of predictive failure models to support the identification of symptoms before a failure event, simulations based on the equipment’s history, scaling optimization against current parameters, having as criteria the costs and availability of the equipment for production. It also includes a component selection tool based on the equipment’s history.


Bidirectional application, hosted on MindSphere IIoT platform, capable of communicating with the real production cell and with the Digital Twin to extract the required inputs for OEE calculation, and return to the MLStudio and real process, the previously calculated indicators for a determined time interval. This bi-directional application will be used to automatically compare production sequences and validate the improvements introduced by Smart Recipes to the optimized virtual production sequences, and therefore to the real production process.

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