Paris, November 8, 2021 - METRON is excited to announce the launch of its new digital tool, EnergyLab, which democratizes the use of Data Science for energy professionals.
EnergyLab is the latest workspace in the METRON-Factory platform, which helps industrial groups to reduce their energy consumption and carbon footprint. Overall benefits include a boost in productivity, reduced costs, and improved business outcomes.
This Data Science tool, which natively integrates all data collected by the platform, allows for users to explore and manipulate complex and vast amounts of useful information without advanced computer knowledge. Complex data from industrial equipment becomes easier to handle.
With EnergyLab, users can explore and model diverse industrial data, which include internal meters from different processes or utilities, as well as external information such as the weather forecast and energy costs in fluctuating markets. By aggregating the data collected from different sources, energy professionals can put them into perspective in order to gain deeper insights and predict the behavior of their factories.
Accessible to all, EnergyLab offers a simplified approach to data science and allows users to:
Create models with an easy-to-use visual tool that requires no coding
Preview and explore data intuitively to better understand your plant behavior and make insight-driven decisions
Create baselines (models used as a reference to predict consumption) quickly and easily, from data exploration to live deployment
This will allow energy professionals to easily:
- Identify all plant influencing parameters.
- Anticipate energy consumption and demands.
- Create their own reference models with historical and live data.
- Deploy models in real time to detect anomalies and drifts.
“EnergyLab is an interesting tool that allows us to better visualize and analyse all the data collected by METRON’s digital platform. It is a way to determine specific factors which influence the energy consumption of your equipment. When these factors are identified, you can then make your own energy baseline that will allow you to monitor the energy efficiency of these processes.”