Data-driven decision support for furnace loading in steel tempering: a machine learning approach based on industrial operations

Keyphrases

• Machine Learning Based 100%
• Industrial Operation 100%
• Machine Learning Approach 100%
• Data-driven Decision Support 100%
• Model Use 50%
• Performance Prediction 50%
• Steel Production 50%
• Electric 50%
• Total Weight 50%
• Load Configuration 50%
• Load Cycle 50%
• Practical Guidance 50%
• Experience-based 50%
• Driven Approach 50%
• R2 Score 50%
• Load Scenarios 50%
• Post-processing Analysis 50%
• Production Data 50%
• Multi-output 50%
• Data-driven Framework 50%
• Holding Duration 50%
• World Production 50%
• Furnace Operation 50%
• Gradient Boosting Regressor 50%
• Partial Dependence Plot 50%
• Industrial Furnace 50%
• Temperature Duration 50%
• Subjective Decision Making 50%
• Covering Dimension 50%
• Irregular Loading 50%
• Decision Support Model 50%
• Feature Importance Ranking 50%
• Xtreme Gradient Boosting 50%
• Block Dimensions 50%
• XGBRegressor 50%

Engineering

• Learning System 100%
• Learning Approach 100%
• Process Parameter 66%
• Limitations 33%
• Forging 33%
• Loading Cycle 33%
• Regressors 33%
• Target Level 33%
• Input Feature 33%
• Industrial Furnace 33%
• Production Data 33%