Laboratory for Automation and Measurement

On 4 November 2025, Assoc. Prof. Željka Ujević Andrijić participated in the Croatian Symposium on Artificial Intelligence with a lecture entitled Application of Machine Learning in Chemical Engineering. The Symposium was organized by the Croatian Academy of Sciences and Arts. She addressed methodological and practical aspects of applying machine learning methods in chemical engineering, with particular focus on data preprocessing and ANN architectures. Through selected examples, the lecture highlighted applications of machine learning in process monitoring, soft sensor development, predictive maintenance, and quality control.

Members of our team have published a scientific paper in the journal Sensors entitled Data-Driven Fouling Detection in Refinery Preheat Train Heat Exchangers Using Neural Networks and Gradient Boosting. The paper presents machine learning–based models that address a key challenge related to energy efficiency and operational reliability under dynamic operating conditions. This publication supports ongoing research on intelligent sensors, data-driven diagnostics and the application of AI in industrial practice. Link: https://www.mdpi.com/1424-8220/25/16/4936

We participated in the ECCE Congress, 8–10 September 2025, with two poster presentations Machine learning models for fouling detection in industrial heat exchangers and Modelling of the green hydrogen production process by anion exchange membrane water electrolysis.

At the Open day of the Faculty of Chemical Engineering and Technology we took part in the workshops: Application of Infrared Thermography and Production of Green Hydrogen . In the workshops, we showed how hydrogen is produced by electrolysis, what applications there are and what challenges need to be overcome during production. We also demonstrated the principle of non-contact temperature measurement with an infrared camera using examples from industry.

Our team has published a paper entitled Monitoring of Heat Exchangers in Preheat Trains Using Neural Networks . This research paper uses neural networks to explore an innovative method for monitoring heat exchangers. The presented approach provides valuable insights for refinery engineers and can serve as an important tool for the continuous monitoring and maintenance of heat exchangers in industrial environments.

The proof-of-concept project Low-cost green hydrogen production has started in our laboratory. The project is funded by NextGenerationEU . The aim of the project is to develop and build a laboratory system – a scalable integrated process for the production of green hydrogen using AEM water electrolysis. By applying pulse width modulation (PWM) and changing the operating conditions, we will try to optimise hydrogen production.

The CrystAPC project ended on December 15, 2023. On this occasion, the entire team gathered to summarise the results of the project and discuss further research and application of the results as well as commercialisation. We would like to thank all project participants and everyone who supported the realisation of this project.

On December 14, 2023 our research group visited the Faculty of Food Technology in Osijek . Prof. Ačkar , Vice Dean for Science and International Cooperation, was our host. Our group presented the CrystAPC project and gave an overview of the project objectives, approach and current scientific achievements. Professor Ačkar presented the faculty's diverse scientific efforts and shared with us research experiences in the field of food technology. The meeting ended with a discussion on possible future collaboration and knowledge dissemination between the two institutions.

On December 7, 2023, our team visited the University of Applied Sciences FH Campus Wien. The FH Campus is renowned for its close connection to industry, which allows students to gain practical experience and get directly involved in research. During our visit, we had the pleasure of meeting Prof Michael Maurer and his colleagues, who showed us around the classrooms and laboratories of the Bioengineering Department. During the lab tour, a wealth of information and experience was exchanged between the research groups, increasing the potential for future collaboration.

CWT , a spin-off company of the Faculty of Chemical Engineering and Technology , has built a CCS (Carbon Capture and Storage) pilot plant in collaboration with our department on behalf of the South Korean company Carbon Value Co . Our researchers M. Markić, M. Sejdić and J. Sacher were responsible for the integration of the measuring equipment as well as for the PLC programming and the SCADA interface for the process control of the pilot plant. The operation of the plant was demonstrated during the visit by experts from South Korea. The pilot plant will be delivered to South Korea after the final system tuning and optimisation. We expect further joint projects and cooperation in the near future.