Machine learning empowers cleaner cement manufacturing

THE CHALLENGE

Cement production contributes to carbon dioxide (CO2) and greenhouse gas (GHG) emissions at various stages of the manufacturing process. With tightening carbon footprint regulations, organizations proactively seek practical solutions towards cleaner cement production. Reducing CO2 emission requires understanding of the complex energy consumption information during the manufacturing process to address the emissions problem. Company X and materialsIN have combined forces to find energy efficient solutions to address this challenge.

THE TWO-TIERED APPROACH

1. Company X leverages a proprietary carbon accounting and emissions management platform to help customers measure, report, and reduce the carbon footprint of their operations. Company X leverages localized data to address climate change to deliver an expedient, clear carbon footprint report to companies which produce, and or utilize, concrete.

2. materialsIN accelerates manufacturing processes optimization by leveraging a proprietary multi-criteria decision making (MCDM) machine learning (ML) methodology. materialsIN Pro-Opt, the company’s process optimization product, harnesses a proprietary data-driven engine to provide an optimal control-based solution to process-related problems. It empowers customers with information that allows for rapid, optimal, real-time and cost-effective decision-making and enables accelerated innovation in the use of materials and equipment.

   In this instance, materialsIN employs its MCDM machine learning (ML) model to handle the conflicting objectives between cement production, low-carbon fuel usage for energy consumption, and CO2 emissions. The ML model operates within the constraints of low-carbon and high-carbon fuel usage to produce energy consumed during cement production. The end goal is to promote low-carbon fuel usage during various stages of cement production.

THE RESULTS

The combined approach by Company X and materialsIN empowers customers with a technological solution that has a superior predictive capability, and allows organizations to make informed decisions. The MCDM model correlates the energy usage information to the conflicting criteria for cement production and CO2 emission. More importantly, the materialsIN methodology provides multiple energy usage solution space for specific cement production and emission targets. This empowers organizations to make informed decisions on selecting optimized energy efficient solutions for cleaner cement manufacturing.

Prediction of Cement Production and Total Emissions Models

Multi-Criteria Decision Making (MCDM)

Higher cement production correlates to higher fuel usage for energy consumption and CO2 emission. Complying to environmental emission standards to reduce CO2 emission without affecting the cement production is of high-priority to organizations. MCDM simultaneously solves the conflicting objectives that meet desired energy consumption criteria promoting low-carbon fuel sources for energy consumption. materialsIN generates alternative fuel usage for energy consumption solutions to cement production and CO2 emission.