Carbon Re, the company dedicated to reducing industrial manufacturing emissions using AI technology, announced on Tuesday 28th June a new collaboration with the Materials Processing Institute to implement its AI technology to steel production processes.
Carbon Re uses the power of AI in the manufacturing process to find its optimum operating parameters and unlock huge energy efficiencies. The software is built upon the foundation of research from Cambridge University and University College London (UCL).
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The company has performed trials in the cement industry that have exceeded expectations. They showed that its technology can reduce the energy intensity and carbon emissions from cement manufacture by up to 8% and 20%, respectively.
That means its technology saves $2.55 million (£2.1 million) in costs and 140,000 tonnes of CO2 emissions annually for an average cement plant. In steel plants, this would result in $5.2 million (£4.3 million) in cost savings and 60,000 tonnes of CO2 in emissions reduction per plant.
“The Materials Processing Institute has extensive experience in industrial processes, and our collaboration will be invaluable to accelerating the development and commercialization of our product for steel,” said Carbon Re’s CEO and Co-Founder, Sherif Elsayed-Ali.
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“Carbon Re’s mission is to reduce emissions at the gigatonne scale by accelerating the decarbonization of heavy industries such as cement and steel. This is a hugely ambitious goal, but we are confident we can achieve it with the UK’s world-leading AI talent, materials research, and industrial policies,” he also added.
Steel production is a high emissions intensive process involving the transformation of iron ore under very high temperatures, reaching 1,400 degrees Celsius – usually achieved by burning fossil fuels. The industry is responsible for 2% of total UK greenhouse gas emissions.
AI advances in deep reinforcement learning open the door for addressing this problem. Carbon Re technology is based on developing AI that ‘understands’ the thermodynamics of cement or steel making. It learns to operate a given plant using the levers available to a human operator which dynamically optimizes production processes based on variable inputs.
Implementing AI to green technologies is one of many pathways towards achieving the emissions reductions the economy needs to reach net zero. Decarbonizing heavy-emitting industries is a focus for many companies taking part in the race to cut pollution.
