Chinese Cement Producer Reduces Coal and Energy Use 2% Saving $330K Annually with MPC
A chinese cement producer deployed Predictive ML for Energy Management in Metals & Mining. As reported by rockwellautomation.com: $330K annual fuel savings.
Source-reported figures — cited source: rockwellautomation.com
What the chinese cement producer was trying to fix
China's leading cement producer faced mounting pressure to reduce coal consumption and greenhouse gas emissions across its extensive plant network. The Yiyang facility alone consumed approximately 165,000 tons of coal annually at a cost of US$16.5M per year, producing 5,000 tons of clinker per day. Conventional PID loop controls could only manage a limited number of variables in a process where kilns must sustain temperatures above 1,200°C and free lime content must remain within a narrow 1–2% tolerance. Operators were spending 50–70% of their time manually monitoring thermal cameras and adjusting fuel flows, yet thermal efficiency did not improve — leaving significant cost and emissions reduction potential unrealized.
What the chinese cement producer deployed
Rockwell Automation deployed FactoryTalk Analytics PavilionX MPC — a modular model predictive control platform built on supervised machine learning — starting with a pilot at the Yiyang facility before expanding to additional plants. The software integrated with the plant's pre-existing control infrastructure without requiring a full system replacement. By ingesting historical production data, real-time process variables, and laboratory free lime measurements, the MPC models predict how disturbances such as variable coal heat value and recirculated hot air from clinker coolers will affect calciner and kiln temperatures. The system then autonomously adjusts coal additions and setpoints across both kiln and mill operations. Following the successful Yiyang pilot, the solution was extended to at least five additional plants, with five more planned.
Results
The Yiyang plant reduced kiln coal and energy consumption by up to 2%, translating to fuel savings of up to US$330K per year against a prior annual coal spend of $16.5M. Beyond the headline metric:
- CO2 and NOx emissions decreased as a direct result of lower coal burn
- Mill performance improved through better control of raw material inconsistency and clinker grindability
- Operator workload dropped significantly — staff previously dedicating 50–70% of their time to manual temperature adjustments could redirect effort to higher-value tasks
- The pilot demonstrated sufficient ROI to justify rollout across five additional plants, with more deployments underway
Key Takeaways
- MPC outperforms PID in high-variable processes: When kiln control involves cascading interdependencies — fuel quality, recirculated air, calciner temperatures — standard PID loops cannot optimize globally; MPC is required.
- Pilot-first rollout de-risks enterprise deployment: Validating at one facility before scaling to six or more plants is a proven approach for cement producers with large plant networks.
- Energy and compliance goals are not trade-offs: A 2% coal reduction simultaneously cut fuel costs, CO2, and NOx — addressing both economic and regulatory objectives in one implementation.
- Integration flexibility accelerates adoption: Software that connects to existing control systems eliminates the need for costly hardware replacement and shortens deployment timelines.
Evidence for the chinese cement producer's Energy Management deployment
- Reported outcome metrics
- 2 cited below
- Cited source
- rockwellautomation.com
- Last updated
Limitation: The cited source does not identify the company.
Explore Related
Vendor
Details
- Industry
- Metals & Mining
- Use Case
- Energy Management
- AI Technology
- Predictive ML
- Company Size
- Enterprise
- Company
- Chinese Cement Producer
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