# Artificial Intelligence in Metallurgical Engineering: Comprehensive Applications in Microstructure Analysis, Property Prediction, and Process Optimization

By geruganti, sudhakarResearch paper

Resource information

Authors: geruganti, sudhakar
Research area: Artificial intelligence
Publication date: 2026
DOI: 10.5281/zenodo.21550120
Upstream last modified: Aug 25, 2026
License: Creative Commons Attribution 4.0 International
Last record update: Nov 6, 2026

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## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Powered Metallurgical Characterization and Optimization: From EBSD Analysis and SEM Image Recognition to Mechanical Property Prediction and Heat Treatment Optimization"** ### Alternative Title 2 (Microstructure Focus)**"Revolutionizing Microstructural Analysis with Artificial Intelligence: EBSD, SEM, Texture Quantification, Grain Size Estimation, and Phase Fraction Prediction"** ### Alternative Title 3 (Property Focus)**"Intelligent Property Prediction in Metallurgy: AI-Driven Estimation of Mechanical Properties, Fatigue Life, Creep Behavior, and Fracture Toughness"** ### Alternative Title 4 (Process Focus)**"Data-Driven Heat Treatment Optimization and Failure Prediction: AI Applications for Enhanced Metallurgical Processing and Quality Control"** ### Alternative Title 5 (Short & Impactful)**"AI in Metallurgy: From Microstructure to Mechanical Properties - A Comprehensive Review of Eight Critical Applications"** ### Alternative Title 6 (Technical)**"Machine Learning and Deep Learning for EBSD Analysis, SEM Image Recognition, Texture Quantification, Grain Size Estimation, Phase Fraction Prediction, Mechanical Property Estimation, Failure Prediction, and Heat Treatment Optimization"** ### Alternative Title 7 (Physics-Informed)**"Physics-Informed Artificial Intelligence for Metallurgical Characterization: Integrating Domain Knowledge with Data-Driven Approaches for Enhanced Prediction and Optimization"** ### Alternative Title 8 (Application-Focused)**"Transforming Metallurgical Engineering with AI: Automated Characterization, Predictive Modeling, and Intelligent Process Optimization"** ### Alternative Title 9 (Industry-Focused)**"AI-Enabled Quality Control and Process Optimization in Metallurgy: From Microstructural Analysis to Mechanical Property Prediction"** ### Alternative Title 10 (Comprehensive Review)**"Artificial Intelligence Applications in Metallurgical Engineering: A Systematic Review of Microstructure Analysis, Property Prediction, Failure Analysis, and Process Optimization"** --- ## SUBTITLE OPTIONS ### Subtitle 1**"A Comprehensive Examination of Machine Learning and Deep Learning Applications for EBSD Analysis, SEM Image Recognition, Texture Quantification, Grain Size Estimation, Phase Fraction Prediction, Mechanical Property Estimation, Failure Prediction, and Heat Treatment Optimization"** ### Subtitle 2**"From Microstructural Characterization to Process Optimization: How Artificial Intelligence is Transforming Metallurgical Engineering"** ### Subtitle 3**"Integrating Physics-Informed Machine Learning, Deep Learning, and Explainable AI for Enhanced Metallurgical Analysis and Decision-Making"** ### Subtitle 4**"Opportunities, Challenges, and Future Directions for AI-Driven Characterization, Property Prediction, and Process Control in Metallurgy"** ### Subtitle 5**"Bridging the Gap Between Microstructure and Properties Through Artificial Intelligence: A Comprehensive Framework for Metallurgical Applications"** ### Subtitle 6**"Accelerating Materials Development and Quality Control Through AI-Enabled Characterization, Prediction, and Optimization"** ### Subtitle 7**"A Strategic Roadmap for Implementing AI in Metallurgical Laboratories, Manufacturing Facilities, and Research Institutions"** ### Subtitle 8**"Leveraging Machine Learning, Deep Learning, and Physics-Informed Models for Next-Generation Metallurgical Engineering"** ### Subtitle 9**"From Grain Boundari