A North American company involved in machine learning (ML) to optimize manufacturing processes is using the DataHub to make their connections. The are using two ways to connect the various processes to the DataHub: custom connections via the DataHub APIs, and OPC. The DataHub then sends the data over the network in real time and logs it into the machine-learning database.
The DataHub offers the company the flexibility to keep their ML system separate from their customers’ equipment and to access multiple OPC servers or program instances, if necessary. The real-time, bidirectional connection supports read and write operations, and the Datahub’s Database Store and Forward feature ensures that no data is lost whenever the network is down and/or the ML database is not available.