International Conference on Thermo Mechanical Processing - TMP 2026

Session

Intelligent Manufacturing

21 Oct 2026, 09:00

Austria Trend Parkhotel Schönbrunn

14. Prediction of Mechanical Properties in Automotive Hot-Rolled Steel Coils based on Position-Specific Cooling History and Process Data Mapping

Dr JAEHYUN CHOI (POSCO)

21/10/2026, 09:00

Intelligent Manufacturing

Oral Presentation

In the modern steel industry, using large process datasets to improve quality control and production efficiency is an essential engineering task. This study focuses on predicting the main mechanical properties—yield strength (YS), ultimate tensile strength (UTS), and elongation—of hot-rolled steel coils for automotive parts. For these components, consistent material quality is critical for...

64. Through Process Modelling of Steel Production in Štore-Steel Company

Prof. Božidar Šarler (University of Ljubljana)

21/10/2026, 09:20

Intelligent Manufacturing

Oral Presentation

A part of the digitalisation efforts in the steel industry concerns the numerical optimisation of the steel production chain to increase quality, productivity, and sustainable production. We present the computational modelling of the steel processing route at Štore-Steel, comprising continuous casting, controlled cooling, annealing, reheating, reverse and continuous hot rolling, cooling bed,...

1. Artificial Intelligence Empowered Processing of Metallic Materials: Challenges and Perspectives

Prof. Wei Xu (Northeastern University)

21/10/2026, 09:40

Intelligent Manufacturing

Oral Presentation

Artificial intelligence is increasingly reshaping metallic materials design by accelerating exploration beyond conventional trial-and-error approaches. However, purely data-driven models often suffer from limited interpretability, excessive data requirements, and poor generalization across different alloy systems/processing routes. This study presents a physically guided AI framework for...

10. A Hybrid AI Approach for Rolling Force Prediction in Plate Mills: Integrating Machine Learning Technique with Metallurgical Simulation Variables

Mr Jackson Carvalho (CBMM)

21/10/2026, 10:00

Intelligent Manufacturing

Oral Presentation

Accurate rolling force prediction in flat hot rolling is essential for precise gap control, shape stability, and equipment protection, operating within mill power and force limitations. In practical hot rolling operations, the prediction of rolling forces is challenged by the combined effects of evolving deformation geometry and different metallurgical phenomena such as recrystallization,...