How could BRS drive unprecedented levels of profit per mill hour while meeting increasing demand for high quality steel at predictable times, all while conserving the amount of energy consumed?
Dave Stickler, CEO of Big River Steel, has a bold dream of building a FlexMill™ and becoming the world’s first Learning Mill — one that can continuously sense, learn, and improve its processes. With a steel market that is at or near capacity, steel plants need to run at maximum efficiency to compete. Most steel mills, even the newer mini-mills built in the 80s, are run by static business rules put in place decades ago – that’s no way to do business!
The world doesn’t need another steel mill. The world needs a steel mill willing to push the boundaries of what steel can do.
To realize Dave Stickler's vision, each part of the mill’s operation needed to be connected and optimized together – enter Noodle.ai.
For BRS, planning starts with demand prediction, so our Demand Signal AI application was a perfect fit. Combining historical demand patterns with auto production, commodity & security futures, global news, and macroeconomic events unlocked powerful breakthroughs in forecast accuracy for maximum capacity increases.
With more than 50,000 sensors embedded in the mill, opportunities abounded for AI to make improvements. This sensor data plus domain knowledge, existing internal data, and external data led to dynamic prediction of wear rates and useful life on high-expense consumables, like refractory panels and critical assets like furnaces.
Running the electric arc furnace at Big River Steel can be comparable to the energy use of the nearby city of Little Rock. By factoring in time of day, weather, and production needs, Big River Steel can anticipate, plan, and smooth their energy consumption to minimize peak demand usage.