Motor Oil Group: Launching predictive maintenance in support of the digital refinery
Explore Motor Oil Group’s journey with SAP
Motor Oil Group wished to monitor its refinery equipment health and performance, reduce unexpected downtime, and lower maintenance costs. To gain a holistic view of its equipment, the company embraced machine learning and predictive analytics using SAP Business Technology Platform (SAP BTP).
>77
%
accuracy in explaining abnormal events from 120 to 20 hours in advance using root-cause analysis of historical data.
24x7
forward-looking time-series forecasting that enables accurate prediction of future sensor measurements.
Our intelligent data application for predictive maintenance is very accurate. With SAP Business Technology Platform and SAP HANA Cloud, we have a complete view of our refinery equipment that will help us reduce unexpected downtime and lower maintenance costs.
Dimitrios Michalopoulos
Industrial Applications Head of IT Division
Motor Oil (Hellas) Corinth Refineries S.A. (Motor Oil Group)
The Challenge
Using machine learning and predictive analytics to reduce downtime
In any refinery, diligent equipment maintenance is critical to keeping workers safe and operations running at peak performance. Standard preventative maintenance processes only allow technicians to catch a potential problem when doing a scheduled maintenance review.
Motor Oil Group wanted to do more than just prevent abnormal equipment behaviour. It sought to harness sensor data to continuously monitor equipment health and predict potential malfunctions in advance. This would allow the company to avoid unexpected and costly shutdowns of key equipment and lower maintenance costs by addressing possible problems before they occur, so equipment and parts can be fixed rather than replaced. Ultimately, it wished to enhance its existing processes with data-driven predictive maintenance.
Creating a predictive model is an iterative process. By working with Accenture and the Data Science group at SAP, we are using SAP Business Technology Platform to dive deep into our equipment data and understand the right questions to ask to get the insight we need.
Dimitrios Michalopoulos
Industrial Applications Head of IT Division
Motor Oil (Hellas) Corinth Refineries S.A. (Motor Oil Group)
The Solution
Collaborating to implement an intelligent data application for a predictive maintenance powered by SAP HANA Cloud
A data value workshop with the Data Science group at SAP and the refinery maintenance department helped identify opportunities to enhance existing maintenance processes through machine learning and predictive analytics. The use cases were prioritized based on the immediate business value they could provide.
A successful proof-of-concept project analysed four years of data on pressure, temperature, and vibration sensors from three compressors. The model was fed with the sensors’ alarm and trip thresholds to predict when these would be exceeded.
Next, Motor Oil Group collaborated with SAP and Accenture’s Applied Intelligence unit in Greece to implement an intelligent data application. The company used SAP HANA Cloud, application development services from SAP BTP and SAP Analytics Cloud to build predictive models for abnormal events based on sensor data and to provide the results through user-friendly dashboards and e-mail notifications.
The Result
Gaining accuracy in understanding historical and future measurements
Motor Oil Group constantly adjusts models to increase effectiveness and intends scaling to additional equipment assets.
Overall, the company has gained a holistic view of its equipment and benefited from lower maintenance costs and less downtime due to the early notification of abnormal events.
Plus, with a system that learns from its own data, the business benefits from predictions that become more accurate and effective over time.
With our intelligent data application for predictive maintenance on refinery-critical compressors we achieved up to 77% accuracy for explaining abnormal events based on historical data and up to 70% accuracy for predicting future sensor measurements using root-case analysis and time-series analysis, respectively.
Dimitrios Michalopoulos
Industrial Applications Head of IT Division
Motor Oil (Hellas) Corinth Refineries S.A. (Motor Oil Group)
SAP helps Motor Oil Group run better
Key business outcomes and benefits
Featured solutions and services
About Motor Oil Group
Founded in 1970, Motor Oil (Hellas) Corinth Refineries S.A. (Motor Oil Group) is one of the industry leaders in crude oil refining and the sales of petroleum products across Greece and the Eastern Mediterranean region. Its refinery business is complex, and includes widespread ancillary plants and fuel distribution facilities that export to more than 45 countries.
| Industry | Region | Company Size | Featured partner |
|---|---|---|---|
| Oil and gas | Marousi, Greece | >2,900 employees | Accenture plc |
Featured partner
Accenture plc is a multinational professional services company that specialises in IT services and consulting. It has just shy of 700,000 employees worldwide and 7,000 clients served throughout more than 120 countries. It works with 185 partners as well as 89 of the Fortune Global 100.
About Motor Oil Group
Founded in 1970, Motor Oil (Hellas) Corinth Refineries S.A. (Motor Oil Group) is one of the industry leaders in crude oil refining and the sales of petroleum products across Greece and the Eastern Mediterranean region. Its refinery business is complex, and includes widespread ancillary plants and fuel distribution facilities that export to more than 45 countries.
| Industry | Region | Company Size | Featured partner |
|---|---|---|---|
| Oil and gas | Marousi, Greece | >2,900 employees | Accenture plc |
Featured partner
Accenture plc is a multinational professional services company that specialises in IT services and consulting. It has just shy of 700,000 employees worldwide and 7,000 clients served throughout more than 120 countries. It works with 185 partners as well as 89 of the Fortune Global 100.