Patheon FRS Project
Project Industrial Plants With Artificial IntelligenceWe have solved a critical problem for Patheon, a multinational leader in the production of drugs and vaccines: protecting freeze-drying plants and vaccine production from voltage drops that, even if minimal, interrupt the processes damage the products being processed.
We have solved a critical problem for Patheon, a multinational leader in the production of drugs and vaccines: protecting freeze-drying plants and vaccine production from voltage drops that, even if minimal, interrupt the processes damage the products being processed. In AGS we have developed an advanced interconnected system that, in addition to providing the electricity necessary for the operation of plants waiting for the restoration of primary energy or the start-up of auxiliary generators, continually collects and reprocesses data to control and prevent anomalies. This solution meets the requirements necessary to benefit from the National Plan Industry 4.0 and has allowed the customer to obtain significant support in investments, through tax incentives.
This allows you to collect data from all the measuring instruments, save them on an “IoT Gateway” (local computer) that simultaneously retransmits them over the internet to a central server. Here, through an IIoT platform, developed by AGS and named I4.0Board, all the data collected in a series of dashboards are analyzed, processed and displayed.
Thanks to the use of Artificial Intelligence algorithms, based on Machine Learning techniques, preventive and predictive indications on the behavior of the plants and the load used are received, to identify any discrepancies in advance.
The project carried out by AGS for Patheon, active since December 2017, is an example for all companies that want to seize the opportunities related to the “Fourth Industrial Revolution” and get investment support through tax incentives.
HOW IT WORKS
The solution uses 3 UPS - connected in “intelligent parallel” mode - which, in the event of a malfunction of one of the three, divide the load without creating an impact on production. However, the real innovation is the possibility to control and “characterize” the electrical load of the plants, that is to say, to define all the “behavioral” data and to verify the electrical parameters with sensors and instruments connected through a data network.
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