Advanced Data Analytics Transformation

MOL Group

BENEFITS

Enhanced Operational Insight

Real-time data visibility across operations allowed MOL Group to make informed, timely decisions.

Predictive Maintenance

Predictive analytics enabled proactive maintenance, minimizing unplanned downtime and optimizing equipment use.

Improved Efficiency

Streamlined data workflows and empowered teams led to significant efficiency gains and process improvements.

THE SITUATION

As a large-scale energy company, MOL Group faced challenges in harnessing its extensive data to optimize operations. Traditional data analysis methods were often limited and time-consuming, hindering the ability to make timely, data-driven decisions across complex refining and petrochemical processes. MOL Group required a modern solution that could consolidate data from various systems, enable real-time insights, and support predictive maintenance to reduce operational disruptions.

THE SOLUTION

IT Vizion collaborated closely with Seeq to deploy a sophisticated analytics solution, designed to help MOL Group make better, faster operational decisions. Leveraging Seeq’s advanced analytics capabilities, IT Vizion configured a platform that consolidated MOL Group’s data across multiple sources, allowing teams to access, analyze, and visualize information in real time. Through this solution, MOL Group could track key metrics, identify trends, and apply predictive analytics to optimize production and proactively schedule maintenance. IT Vizion also provided training and ongoing support to MOL Group’s teams, empowering them to maximize the potential of this data-driven approach.

András Buti, MOL DR Automation & Process Intelligence Manager, delivered an engaging presentation that highlighted the impact of Seeq’s advanced analytics capabilities on Slovnaft and MolGroup’s operations.

By implementing Seeq’s capabilities, MolGroup has gained critical insights that enhance operational efficiency through data-driven decision-making. Leveraging historical data and machine learning, Slovnaft can now predict necessary maintenance, identifying patterns and anomalies that signal potential valve failures. This proactive approach enables scheduled maintenance, reducing downtime and boosting overall performance.

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CUSTOMER PROFILE

The client is a leading Central European oil and gas company with operations in over 30 countries. Engaged in upstream and downstream activities, including refining, petrochemicals, and retail, MOL Group is committed to driving innovation and efficiency across its operations.

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