Energy Efficient Cement Manufacturing

Project Lead: University of Louisville
Partners: Argos

Member % Cost Share: 50.75%
CESMII % Cost Share: 49.25%
Duration: 6 Months

Problem Statement

Cement manufacturing is energy-intensive (5GJ/t) and comprises a significant portion of the energy footprint of the composite material. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact and lower costs.

Project Goal

Develop smart manufacturing tools for optimized production of cement to reduce energy consumption by 15%.

Technical Approach

Develop smart manufacturing(SM) tools through modeling of rotary kiln along with calciner to achieve reduction in energy consumption. In this project, the Team will extend the prior model developed (both physical and machine learning) for cement Kiln processes to include calciner to support overall energy efficiency. There is a relationship between kiln temperatures and calciner temperatures that must be accounted for in the cement process model. In addition, the degree of calcification of kiln feed and quality cement clinker must be accounted for in the models to allow the significant energy savings predicted by the previous process models to be realized. This is critical in wide-spread adoption by the cement industry.

Deliverables/Outcomes/SM Marketplace 

To be listed at project completion.


Potential Impact

Specifically, this project will showcase energy efficiency in the cement industry by creating a Portland Cement manufacturing process model that includes the calcining process and can be used to save significant energy use (at least 15%). The calcining process can use a significant amount of energy, especially in short cement kiln configurations and often the integrated natures of the kiln and the calciner can work against energy efficiency measures implemented in the kiln system.



  • Develop a CESMII platform profile that will allow other cement producers to acquire the advisory programs, calibrate the process models and use these to save energy in their specific processes

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