University of Twente Student Theses
Maintenance Optimization Through predictive Maintenance: A Case Study For Damen Shipyards
Dekker, K.J. (2020) Maintenance Optimization Through predictive Maintenance: A Case Study For Damen Shipyards.
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| Abstract: | We use predictive modelling techniques to predict the remaining useful life of critical components on ships. Specifically, we use a recurrent neural network and a gradient boosting tree to predict the remaining useful life of the fuel separator. We found the gradient boosting tree to be a suitable model for this prediction task. When optimizing a maintenance threshold, the boosting tree outperforms a baseline time-based preventive maintenance model (a 1.4% cost reduction). |
| Item Type: | Essay (Master) |
| Clients: | Damen Shipyards, Gorinchem, Netherlands |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 01 general works, 50 technical science in general, 58 process technology, 85 business administration, organizational science |
| Programme: | Industrial Engineering and Management MSc (60029) |
| Link to this item: | https://purl.utwente.nl/essays/80852 |
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