As the industry most directly responsible for global development, the cement industry can’t afford to slow down. But as the industry currently responsible for 8% of global emissions, they can’t afford to grow emissions with production or even continue at the rate they’re at. In lieu of a complete process redesign, the industry is looking to emerging technologies to close the gap on their carbon reduction commitments. One of the most promising technologies harnesses the forefront of AI innovation integrated with existing controls infrastructure for closed loop process optimisation.
Navigating the Nuance of Cement Processing
The cement industry presents unique challenges in process optimisation due to inherent raw material availability and variability. The combination of these can lead to irregular clinker quality, reduced productivity, and a resultant reduction in process energy efficiency. This instability is compounded by the push to incorporate a greater percentage of lower carbon alternative fuels. While offering a lower carbon opportunity, the new fuel sources are less understood and lack the well-defined first principles relationships required by traditional advanced control solutions.
A Modern AI Approach
A new class of optimisation technologies has emerged which capture the nuance of each specific cement operation by starting from the plant’s historical process data. Years of historical process data are paired with cutting-edge AI modelling techniques resulting in robust process models that capture the details of each site’s specific operating quirks, without relying on the existence of, and assumptions behind, first principles relationships. These models are transformed into controllers, which learn the optimal economic actions to take in any situation through offline reinforcement learning. In a matter of hours, the plant sees every combination of process conditions the plant has experienced plus many more hypothetical scenarios, developing experience equivalent to an operator present for every minute of historical plant operation.
Case studies demonstrate the promise of AIO
Closed Loop AI Optimization (AIO) technology has demonstrated value in multiple areas of cement processing. The following case studies represent some of the highest potential optimisation opportunities in a cement plant.
1.Maximising Pyro-processing System Efficiency
Lab-measured variables like free lime concentration have historically been challenging to estimate using process sensor data due to nonlinearities. Imubit has operationalised accurate free lime inferentials, enabling real-time quality tuning that increases kiln stability and improves process reliability and uptime. The benefits compound as improved clinker quality reduces the load on downstream cement mills, alleviating throughput constraints. In a global top 5 cement company, this has resulted in a 1% throughput increase alongside significant reduction in clinker quality standard deviation. The increased stability has the plant questioning the status quo, pushing closer and closer to the plant’s true operating limits.
2.Minimising Downstream Energy Intensity
One of the best strategies to accelerate decarbonisation efforts is to couple them with quality improvements. By providing adequate process stability, that eliminates the need for conservative over-burning of clinker. Imubit AIO can deliver more consistent, higher quality clinker that reduces the energy consumption requirements in grinding stages. Across medium and large cement plants, this has resulted in a significant reduction in fineness standard deviation contributing to lower clinker factor and provided an average of 2% energy efficiency improvement in the grinding stages.
3.Eliminating Finished Quality Giveaway
Variable clinker quality can present challenges for cement mill optimisation towards maximised throughput within fineness specification limits. A key step in Imubit’s model development process involves learning all the nonlinear relationships between manipulated, controlled, and disturbance variables, and applying those learned relationships to automate decision-making in closed loop. Leveraging the learned nonlinear relationships between mill throughput and separator speed, Imubit makes real-time adjustments towards the economic optimum, pushing throughput while maintaining integrity of the fineness specification.
Industry Players Must Adopt, or Risk Being Left Behind
These trends in technology adoption indicate a shift towards a more sustainable, efficient, and adaptable cement industry. Producers that successfully integrate these strategies will be better positioned to navigate the challenges and opportunities ahead.
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About Imubit:
Trusted by 7 of the top 10 U.S. refiners and deployed in over 90 applications, Imubit leads the way in Closed Loop AI Optimisation (AIO). The Imubit Optimizing Brain™ Solution democratises AI for engineers, empowering customers to build and leverage their own multipurpose models to tackle complex challenges, boost margins, and reduce emissions. Imubit’s domain experts work hand-in-hand with customers to accelerate digital and workforce transformation, ensuring future-proof operations. Learn more at www.imubit.com.