|Summary||Data-driven alarm prediction using sensor data|
|Supervisor||Hadi Fanaee-T(www.fanaee.com), Mahmoud Rahat|
This is a fantastic opportunity to work with Alfa Laval, a world's leader and pioneer in producing separator machines. This project aims to investigate the application of Machine Learning for analysis of onboard sensor data from separator machines. The separators purify oil and water supplies onboard marine vessels.
The main objective of this project is to predict and analyze alarms of separator machines. The automation software of machines produces faults and warming messages during its operation. Currently, these alarms are produced based on fixed, predetermined thresholds. It is interesting to explore timeseries forecasting methods and machine learning models to predict alarms beforehand. The benefits of more in-depth exploration are both in terms of technical and business value, including among the others: property damage control, oil Loss reduction, overall machine health, and fuel quality control.