Durst develops AI predictive for maintenance in print production facilities

Durst has joined the EU-funded project PREMISE with the Free University of Bozen-Bolzano (unibz) to develop software that enables predictive maintenance in print production facilities. The company has been calculating appropriate algorithms that make predictions about maintenance requirements. The combination of intelligent sensors and software evaluation for component and machine data forms the basis for predictive maintenance—the detection of error states or the need for service or replacement of spare parts ‘in advance’ so that production can be adjusted accordingly.

With the PREMISE project, durst goes one step further and uses AI (Artificial Intelligence) methods to make these predictions and interventions before an emergency even more efficient and to be able to apply them even to complex, causal relationships. This is a decisive advantage, especially in times when international traffic is restricted. A manufacturer of snowmaking systems, TechnoAlpin, was selected as a further industrial partner. The project, headed by Johann Gamper, professor and vice rector for research at the Faculty of Computer Science, aims to develop a technical infrastructure with database technologies that enables predictive maintenance measures on production facilities. The project will run until July 2022 and will be extended until the end of 2022 depending on the status.