Rabbit Miner Ltd. offers comprehensive data mining and process systems engineering services. We are specialized in process optimization, data science applications, supply chain management, and Industry 4.0 solutions. Our potential partners and customers are the industrial companies open to new data-driven optimization techniques. Our experience in data science as well as in process systems engineering makes us the ideal innovation and R&D service partner to solve your process optimization problems.
What We Do
AI-BASED ALARM MANAGEMENT
Risk mitigation by Artificial Intelligence
RABBIT MINER IN TOP 50 IN BIG BANG STARTUP COMPETITION
The process systems engineers
According to a recent study, companies who can effectively quantify gains from analyzing data, report an average of 10 % reduction in costs each year, moreover, data analysis helps companies investing capitals more efficiently.
Therefore, industrial plants and production sites record more and more data of the production due to the increasing sensor technology.
However, only a minority of this data is used to increase production efficiency and excellence.
years experience in data-based solutions
The technological data collected by WebScada systems, which have existed and been in operation for decades, offer a wealth of opportunities that can be exploited by machine learning algorithms based on artificial intelligence, which have already been proven useful in the financial and telecommunications sectors.
The Rabbit Miner and Skyline apply a new data mining based research and development project to the Hungarian funding.
The aim of the Artificial Intelligence (MI Coalition) is to put Hungary at the forefront of artificial intelligence developments and applications in Europe and to become an important member of the international MI community.
Gyula graduated with bachelor’s (2016) and master’s (2017) degree in chemical engineering with a specialization in process engineering from the University of Pannonia. His work interest covers the areas of goal-oriented optimization, event analysis and data science applications in process mining. His current work focuses on the applications of process mining tools in alarm management for the improvement of process safety.
Tamás graduated with a bachelor’s degree in Mechanical Engineering (2015) and Engineering Information Technology (2015) and master’s degree in Mechatronical Engineering (2016). His work interests cover the areas of process mining algorithms, Discrete-event simulators and supply chain management. His current work focuses on Industry 4.0 (Discrete Event simulators, Connected Factory, Supply Chain management) and Big Data.