Predicting the status of machines with vibration data
| Title | Predicting the status of machines with vibration data |
|---|---|
| Summary | Predicting the status of Alfa Laval's separator machines with vibration data |
| Keywords | machine learning, predictive maintenance, time series analysis, vibration analysis |
| TimeFrame | |
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| Author | |
| Supervisor | Hadi Fanaee-T (www.fanaee.com), Mahmoud Rahat |
| Level | Master |
| Status | Open |
This is a fantastic opportunity to work with Alfa Laval, a world's leader and pioneer in producing separator machines. They are collecting large amount of data on vibration of rotating parts. The idea is to use the vibration data to predict the status of the machines. If the status of the machine is known, it can be predicted when next service is needed and if parts needs to be exchanged. The condition of the machine is very important to the customer to make sure there will be no unplanned stop in the production. The machines are used in important processes in various industries as food, cleaning of water, refineries and pharma. The application is used by Alfa Laval to make reports that are sent to the customer on a regular basis. There are hundreds of machines worldwide collecting data for reporting. The machine has five measurement points and each measurement point has a number of frequency ranges to be measured.
