BeChained

They reduce operating costs in industrial manufacturing (e.g., metal & steel, paper, food, chemicals…), making production processes more energy efficient, such as thermal systems, air compressors, and water management.

They built a Process Optimization Solution based on Reinforcement Learning that learns from real-time data, identifies machine adjustments, and can implement improvements in production.

Finally, it converts this energy efficiency into demand flexibility to generate new revenue streams for industrial customers in demand-side response markets (i.e., mFRR, aFRR…).

Their technology is deeply integrated within a factory and is fed by energy data, production data (ERP and temperature), and machine settings (e.g., SCADA, MES, PLC, OPC-UA…).

In the cloud, their (patented) Reinforcement Learning models learn in real time how processes are performing, based on environmental data and production peculiarities. Then, they choose the settings that minimize energy resources and prevent possible events (predictive maintenance).

Finally, they generate instructions to be executed on the machines via OPC-UA.

They use Digital Twins of processes and machines to characterize a production line. This holistic vision allows them to create the path for the intelligent and autonomous factories of the future.