The Josef Ressel Center for Intelligent Thermal Energy Systems focuses on four Research Areas (RA)
RA1: Expert Systems and Intelligent Report Management
In general, expert systems and intelligent reporting tools are designed to solve complex problems using knowledge bases that are highly dependent on the domain of the application. Thermal power engineers:in industry already have extensive knowledge related to their domains, but they are usually not trained to map these relationships into algorithms. In this research field, we aim to map industry-established methods of fault analysis and decision making into executable algorithms.
RA2: Predictive Maintenance and Control
The recent literature on predictive maintenance deals with very specific questions and specific system configurations. On the other hand, predictive maintenance has been around for decades and has become a productive solution in other highly standardized application areas, such as commercial facility management. Our goal is to transfer the knowledge available in the literature to our industrial applications and add value to the scientific community through the adaptations we develop.
RA3: Optimized operation management and system design
In particular for the manufacturing industry, where several different and complex processes run simultaneously (e.g. cooling and heating of products during production), there are interdependencies between these processes. This means that each device in the process chain controls itself by adapting to a variable requirement of the subsequent process. In a future Factory 4.0, the entire process line will be controlled by a strategic control unit that will allow processes to be scheduled to match the best overall efficiency of the entire plant. In this research field, we particularly want to explore the use of historical data for optimized operations management and strategic system design.
RA4: Technology CV and LCA-based development (considered only in the 1st phase of the project)
In this research area, we propose the development of a life cycle for different technologies (technology CV) that combines historical and current operational data. The necessary time period for historical data, the absolute number of data sets (e.g., the number of sensors required), and the necessary temporal resolution of these data are key issues for the technology CV approach. In addition, exergoeconomics or even life-cycle analysis are promising approaches for the assessment of thermal energy systems. However, these approaches currently lack time-dependent parameters, which we want to obtain for the first time via the technology CV and integrate into the methods.