Smart Manufacturing Controls Reduce Greenhouse Gas Emissions at Cement Plant BENEFITS TO OUR NATION Cement manufacturing comprises a significant portion of the carbon footprint
Project Objective
Develop a Smart Manufacturing control system for cement production by implementing predictive process models, data analytics, sensors and machine learning, The control algorithms will be developed in partnership with ARGOS USA Cement and result in improved energy- efficiencies and product quality.
Benefits to Industry
Concrete is the single most widely used construction material in the world and Portland Cement is a critical component of concrete. The process used to manufacture Portland Cement is energy intensive and comprises a significant portion of the energy budget of cement manufacturing. Over 90 percent of the total cement industry energy use (and CO2 production) involves Portland cement clinker manufacturing. Reducing the energy input of Portland cement clinker production will drastically reduce production costs for cement manufacturers.
Technical Approach
Develop smart manufacturing (SM) tools by modeling rotary kiln and calciner processes to achieve a reduction in energy consumption. Extend prior physical and machine learning models developed for cement kiln processes to include calciner processes to support comprehensive 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.
Accomplishments
- Incorporated the Calciner and Kiln Aspen model into the process model
- Expanded the predictive control (PC) model to use forward prediction methodologies
- Generated over 3,000 kiln and calciner temperature data points to combine with historic kiln and calciner data to optimize the model
- Deployed the model predictive control (MPC) at the Argos Roberta cement plant
- Developed cement kiln profiles for integration to the CESMII Smart Manufacturing Interoperability Platform (SMIP)
- Demonstrated 28% reduction in energy input while maintaining product quality and improving production rates
Deliverables
- Delivered new cement manufacturing process numerical model
- Deployed advisory system nonlinear model predictive control (NMPC) at Argos Roberta plant, showing good agreement between predicted and measured performance
- Delivered Cement Kiln SM Profile
Reusable Outcomes
- Model Predictive Control (MPC) for cement manufacturing
- Cement Kiln SM Profile