The Answer Lies In AI

Operating a cement kiln has always involved balancing numerous and often conflicting priorities, from optimising production levels and maintaining consistent product quality to controlling costs, ensuring reliability, and meeting strict environmental regulations. But now, the need to decarbonise is pushing the industry to find innovative ways to produce cement, meaningfully changing the production environment. With the introduction of new fuels, new raw materials, and hardware like CCUS units becoming standard, cement production will continue to evolve, bringing evermore complexity and variation into an already complex system.

Meanwhile, the advanced process control (APC) systems that have traditionally provided the automation layer of cement manufacturing have not kept pace with this innovation. The cement industry needs a powerful solution to tackle these new challenges, and AI-powered process control is leading the way.

How is AI process control different from APC?

The fundamental difference between AI process control and APC is in the type of models that form the basis of the respective technologies. APCs are hard-coded with simpler models like model predictive control and fuzzy logic that are constrained by computational capability, whereas AI process control uses more advanced machine learning based models that are effective for complex chemical processes. AI models are also developed using a wider range of process data and a longer timeframe of historical data, meaning that the overall capabilities of AI models are greater than those that underpin APCs.

The fixed approach of APCs also means that they suffer from performance deterioration over time due to model drift. AI solutions overcome this with cloud-based self-learning and self-tuning encoded in the software, maintaining peak operational performance over the long term.

This difference in modelling complexity ultimately changes the strategy the AI or APC uses to control the process. Think of these two strategies as stabilisation and optimisation. APC systems are masters of stabilisation. They react to incoming plant data and make control changes to maintain consistency at specific process targets e.g. temperature or oxygen levels. AI, on the other hand, excels at optimisation. By generating new information that cannot be measured, or is not typically measured, based on real time conditions, AI optimises plant operations to achieve higher-order objectives, such as reducing specific heat consumption or minimising fuel costs.

The beauty of these two strategies is that they are complementary. AI can provide a dynamic layer of intelligence on top of an APC to adjust and optimise operations in response to changing conditions while maintaining peak operational performance over the long term.

That is why both ABB and FLSmidth Cement have partnered with Carbon Re. AI and APC deliver significantly better performance – faster, smarter, and more adaptive cement production.

Together, these solutions significantly enhance cement production efficiency and reduce emissions, setting industry benchmarks for AI adoption and sustainability practices.

AI process control in practice at Çimsa

The Turkish cement and building materials company, Çimsa, deployed Carbon Re‘s AI platform to improve operational efficiency.

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Read the article online at: https://www.worldcement.com/special-reports/19082025/the-answer-lies-in-ai/