International Cement Company Increases Throughput 5.7% and Reduces Power 4% with Advanced Process Control

An international cement company subsidiary deployed Predictive ML for Process Optimization in Industrial Machinery. As reported by rockwellautomation.com: 3.5 KWh/ton power consumption reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
3.5 KWh/tonPower consumption reduction
38%Reduction in cement quality standard deviation

Source-reported figures — cited source: rockwellautomation.com

What the international cement company subsidiary was trying to fix

A subsidiary of an international cement company with revenues over $500 million sought an advanced process control system to maximize efficiency, enhance quality, minimize process upsets, and decrease energy costs on two finish mills at its headquarters facility.

What the international cement company subsidiary deployed

Rockwell Automation deployed FactoryTalk Analytics with closed-loop multivariable predictive control on two cement finish mills. The solution combined steady-state optimization with model predictive control and dynamic process modeling, managing setpoints and transitions in real-time.

Results

Throughput increased on both mills — one by a notable margin and the other by 5.7% — with finish mill production increasing 5% overall. Power consumption was reduced by 3.5 KWh/ton of cement produced, with total mill motor power also meaningfully reduced. Product quality improved with standard deviation in cement reduced from 130 to 80 — a 38% reduction — achieved in just four months.

Key Takeaways

• Model predictive control delivers simultaneous improvements in throughput, energy, and product quality • Phased ROI validation programs reduce financial risk for manufacturers evaluating advanced process control • Dynamic process models outperform static expert system solutions for complex non-linear processes like cement milling

Evidence for the international cement company subsidiary's Process Optimization deployment

Reported outcome metrics
2 cited below
Last updated

Limitation: The cited source does not identify the company.

Share:

Details

AI Technology
Predictive ML
Company Size
Enterprise
Company
International Cement Company Subsidiary

Have a similar implementation?

Share your customer's AI results and link it to your vendor profile.

Submit a case study →