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Data Driven wheel set usage prediction and inventory control

Koopman, M.P. (2021) Data Driven wheel set usage prediction and inventory control.

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Abstract:Train wheels are a critical part of train operations. To decrease operational costs, more knowledge about the degradation process and demand rates is needed. With the help of Multiple Linear Regression, we are able to predict future degradation and with that demand for new wheel sets as well.
Item Type:Essay (Master)
Clients:
Arriva, Zutphen, Nederland
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:58 process technology
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:http://purl.utwente.nl/essays/86298
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