Laboratory for System Health & Risk Management led by Professor Byeng Dong Youn of Department of Mechanical Engineering at Seoul National University's was participated in the PHM Data Challenge held at the Asia Pacific Conference of the Prognostics and Health Management 2021 at Ramada Hotel in Jeju, Korea September 8-11, 2021 and achieved the feat of winning all 1st, 2nd, and 3rd places.

The PHM Data Challenge is an international competition held annually by the 'PHM Society', a world-renowned academic society in the field of predicting and managing the soundness of industrial facilities. In this competition, research teams from renowned companies/schools/research institutes in Asia Pacific participate in the competition to analyze actual industrial data occurring at industrial sites every year, and to predict the type of failure and the time of failure of the facility. In this contest, Professor Yoon's lab team, "HIT" team and "JKL" team jointly won the 1st Place Winner, and OnePredict's "Pandamon" team won the 3rd Place Winner.

This year, two tasks were presented: 1) restoring consecutive missing values ​​of vibration data acquired from 'Oil-injection Screw Compressor', and 2) diagnosing the condition of the facility based vibration data. In the competition, the task of restoring long-term missing vibration data that could not be solved by methods such as interpolation or moving average method was achieved with an approach that fused the knowledge of the mechanical engineering domain with the method of designing a deep learning structure suitable for the problem. Professor Yoon's team participated notly in this competition but also in industry data analysis competitions held by related societies such as IEEE and the government, and was selected as a winner a total of 14 times in the past 7 years.

Regarding this award, Professor Yoon said, “Industrial data is rapidly increasing with the rise of the 4th industrial revolution, and the economic effect of industrial facility availability, manufacturing quality, industrial safety, and productivity improvement made possible through industrial data analysis and prediction is significant. It is more than 50 trillion won annually,” he added.