The system lives both on-shore (on cloud) and off-shore (on the vessel). The on-shore part of the solution is devoted to regularly read fresh generator’s data synced from the vessel to the Azure cloud, and together with CMMS events automatically retrains a machine learning model every month. Once trained, the new model is then moved off-shore to perform online predictions every 12 hours. The model advices if an intervention is needed and explains what generator sensors are driving the prediction in order to support the maintenance intervention. The results are visualized through dashboards: on-shore implemented with Power BI, and off-shore with ChartJS.