Smart Management and Reliability of Energy Infrastructure
We help companies in the energy sector to anticipate and adapt to major technological changes with confidence. We see ourselves as true partners who take all aspects of technological challenges into account from a long-term perspective.
Energy players need to accelerate their transformation towards low-carbon models. This means optimizing the energy performance of existing facilities, developing alternative energies (hydrogen, batteries) and implementing monitoring solutions to measure and reduce CO2 emissions.
Energy sites (refineries, petrochemical plants, power stations) operate in ATEX environments with explosive risks. The cyber-security of industrial facilities and strict compliance with safety standards are non-negotiable imperatives to protect people, assets and the environment.
The energy industry needs to deploy data-driven approaches at scale: interoperability of solutions, centralization of data, real-time supervision, predictive maintenance and artificial intelligence to optimize decision-making. The challenge is to marry the IT and OT worlds, while guaranteeing site resilience.
Energy manufacturers are looking to improve the overall performance of their equipment and processes: predictive maintenance to anticipate breakdowns, optimize energy costs, make production lines more reliable and reduce unplanned stoppages.
Project Description & Challenges
Industrialization of Machine Learning Models
Development of a modern data platform capable of running several thousand machine learning models on data generated by this energy provider’s equipment and its customers.
> Detection of anomalies in this equipment.
Expertise
Data
Machine Learning
