A Multi-Plant Machine Learning Framework for Emission Prediction, Forecasting, and Control in Cement Manufacturing

This study develops a machine learning framework to predict, forecast, and control NOx emissions in cement manufacturing, a major source of industrial air pollution. The framework utilizes large-scale operational data from multiple plants, significantly improving prediction accuracy and enabling proactive operational adjustments to mitigate pollution.