Gabor Prinzz

Gabor Prinzz is a Researcher at the University of Applied Sciences Wiener Neustadt, affiliated with the Institute of Industrial Engineering and Management. His work focuses on integrating historical maintenance data with real-time sensor information to optimize industrial processes.

Research projects led by Prinzz include:

• ReMAIntAIn: Combines object- and order-oriented data with non-stationary dynamic Bayesian networks (nsDBN) to predict component failures and resource-efficient maintenance measures in high-resource-consumption industries like aluminum casting.
• DigiProTrain: Develops Industry 4.0 training courses in learning factories, enhancing educational accessibility via the EIT Manufacturing Marketplace.
• IntelliProPS: Integrates machine learning with classical production planning methods to address volatility in manufacturing, funded by FFG's COIN program.

  His research intersects industrial engineering, predictive maintenance, and AI-driven automation. Prinzz collaborates with institutions like TU Wien and companies such as Fried v. Neuman GmbH and Mesify Solutions GmbH.