iTAC shows how manufacturing can benefit from the Artificial Internet of Things


Montabaur. Combining AI with IoT (AIoT) opens up new potential for creating value from data. The focus is on collecting, analyzing and interpreting data from machines and sensors with the help of an MES/MOM. In this way, predictions can be derived and self-learning processes can be developed. The MES/MOM specialist iTAC (www.itacsoftware.com) demonstrates the possibilities for implementation.

“With the Internet of Things and a multitude of networked machines, more data is available. However, this data is worthless if it cannot be used in decision-making processes. It must therefore be processed and evaluated by AI applications as quickly as possible. Artificial intelligence can also draw comparisons with other processes, systems and their data and, by learning from experience, independently solve future tasks, avoid errors and optimize processes,” explains Martin Heinz, board member of the iTAC Software AG.

The IoT structure therefore needs artificial intelligence, which in turn needs the Internet of Things as a source of data. The iTAC.IIoT.Edge software, a part of the MOM system (Manufacturing Operations Management), combines IIoT data with MES data to form flat data structures for a real time analysis.

“Machine learning and AI-based applications in the field of analytics enable more sophisticated and higher-quality analyses than conventional technologies. Artificial intelligence can, for example, find complex patterns in the data and make predictions,” explains Martin Heinz.

By using iTAC’s edge solution, numerous ML/AI use cases can be developed for advanced and digitalized manufacturing, for example in the area of prediction. The corresponding monitoring of machine and sensor data makes it possible to predict machine failures (reduction of almost 70%).

The possibilities are numerous. iTAC offers a use case library that enables customers to implement applications quickly and easily.

iTAC Software AG
Alina Leber
+(49)26021065211
[email protected]



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