Case Study: Motor Oil Group achieves predictive maintenance and reduced unexpected downtime with SAP HANA

Motor Oil Group Launching Predictive Maintenance in Support of the Digital Refinery

Motor Oil (Hellas) Corinth Refineries S.A., founded in 1970, is a leading crude‑oil refiner and fuel exporter serving more than 45 countries. Faced with the limits of scheduled preventative maintenance, the company wanted to harness sensor data and machine learning to continuously monitor equipment health and predict malfunctions days in advance to avoid costly unplanned shutdowns and reduce maintenance costs.

Working with SAP and Accenture, Motor Oil piloted a predictive‑maintenance solution on critical compressors using SAP Business Technology Platform (SAP HANA Cloud, SAP Analytics Cloud, SAP Extension Suite) to ingest time‑series sensor data, build models, and deliver dashboards and email alerts. The proof‑of‑concept—analyzing years of pressure, temperature, and vibration data—achieved over 77% accuracy in explaining abnormal events 20–120 hours ahead, strong 24‑hour sensor forecasts, and a holistic, self‑learning system that improves predictions, reduces downtime, and lowers maintenance costs as it scales.

Motor Oil Group

Dimitrios Michalopoulos

Industrial Applications Head of IT Division