Machine Learning Algorithm to Predict CO<sub>2</sub> Using a Cement Manufacturing Historic Production Variables Dataset: A Case Study at Union Bridge Plant, Heidelberg Materials, Maryland

Machine Learning Algorithm to Predict CO<sub>2</sub> Using a Cement Manufacturing Historic Production Variables Dataset: A Case Study at Union Bridge Plant, Heidelberg Materials, Maryland

This study uses machine learning methods to model different stages of the calcination process in cement, with the goal of improving knowledge of the generation of CO<sub>2</sub> during cement manufacturing. Calcination is necessary to determine the clinker quality, energy needs, and CO&l...

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Bibliographic Details
Main Authors: Kwaku Boakye, Kevin Fenton, Steve Simske
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Journal of Manufacturing and Materials Processing
Subjects:
cement
manufacturing
calcination
CO<sub>2</sub> emission
machine learning
Online Access:https://www.mdpi.com/2504-4494/7/6/199

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