Winning degree project makes rail transport smarter
This year’s Automation Student competition has been decided. Ajna Hodzic and Dzenita Skulj have explored, in their prizewinning degree project, how data analysis and machine learning can reduce costs, predict maintenance and improve efficiency in rail transport.
Ajna Hodzic and Dzenita Skulj were educated at the University of Sarajevo, Bosnia and Herzegovina, within the area of Automatic Control and Electronics. Through an Erasmus+ scholarship they have read their Master’s programme in Embedded Systems at Mälardalen University.
The degree project, Data Driven Anomaly Control Detection for Railway Propulsion Control Systems, has been carried out at Bombardier Transportation in Västerås, where the authors have investigated different methods for monitoring and analysing data collected during the propulsion of trains. Two machine learning techniques – monitored and unmonitored learning – are used to detect deviations and predict potential faults.
The jury’s statement
The prizewinning degree project takes us on an exciting journey in the real implementation of smart industry. With the help of for example deviation detection, early warnings and machine learning, the authors show how rail transport can be made safer, more efficient and more sustainable. The insights presented have the potential to increase the attractiveness of the railway sector but can also increase the opportunities for digitalisation and automation within other sectors.
About the Automation Student competition
To emphasise the importance of a stable regeneration within the field of automation, Automation Region, the Swedish Exhibition & Congress Centre along with the industry organisation Swedish Automation arrange an annual competition for the best automation-related degree project. The award has been presented since 2010 and the prizewinning entry is rewarded with a scholarship of 20 000 SEK.