AI & Machine Learning

Building a "Soft Sensor" for Cement Kilns: Predicting Control Levers with Python

Ali Nemati16 hours ago25 sec read2 views0 listens

A "Soft Sensor" using Python and XGBoost has been developed to predict four critical control variables (Kiln RPM, ID Fan setting, Feed Rate, Fuel Adjustment) in cement kilns based on raw meal chemistry. This predictive model ensures consistent quality and stability by providing precise adjustments that reduce variability and energy consumption, crucial for maintaining optimal plant operations.

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Building a "Soft Sensor" for Cement Kilns: Predicting Control Levers with Python

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