Data-mining and Machine Learning for Materials Engineering in Steel Industry

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Invited Lecture

22.11.2023

Data-mining and Machine Learning for Materials Engineering in Steel Industry

KS

Dr. Kinshuk Srivastava

AG der Dillinger Hüttenwerke

Srivastava, K. (Speaker)¹

¹AG der Dillinger Hüttenwerke

Materials Modelling, Simulation and Data

Werkstofftechnik Stahl

Fertigung und Produktionstechnik

Prozessoptimierung

maschinelles Lernen

Anomalieerkennung

Werkstofftechnik

Physikalische Modellierung

Segregationsanalyse

Wasserstoffinduzierte Rissbildung

Stahlproduktion

Vorschau

32 Min. Untertitel (CC)

Ähnliche Beiträge

Invited Lecture

Optimizing strain prediction and process design of forged parts by modeling and deploying a machine learning surrogate

Matsuo, M. (Speaker)¹; Lopez Santaella, M.¹; Ihne, J.¹; Hartmaier, A.²; Stricker, M.²

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Manufacturing microstructures with desired properties using two machine learning-based approaches for materials design and optimal processing

Morand, L. (Speaker)¹; Helm, D.¹; Iraki, T.²; Link, N.²

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Highlight Lecture

Machine learning for laser powder bed fusion: from process control to materials design

Kosiba, K. (Speaker)¹; Kononenko, D.Y.¹; King, W.E.²; Hufenbach, J.K.¹; van den Brink, J.¹; Chernyavsky, D.¹

Invited Lecture

Active learning for data-efficient optimisation of materials and processes

Todorović, M. (Speaker)¹

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

The bainite calculator: A graphical model for Bayesian optimization of carbide free bainitic steels

Schuscha, B. (Speaker)¹; Brandl, D.¹; Mücke, M.¹; Romaner, L.²; Scheiber, D.¹

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Physics informed neural networks for permeability predictions of fibrous microstructures

Korolev, D.¹; Cassola, S. (Speaker)²; Hintermüller, M.¹; Schmidt, T.²; Duhovic, M.²; May, D.²

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Invited Lecture

AI supported quality control in the steel industry

Schäfer, M. (Speaker)¹

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Empowering Manufacturing through Adaptive Experimental Design and Machine Learning

Nenchev, B. (Speaker)¹; Strickland, J.¹

Invited Lecture

Impact of Artificial Intelligence on Failure Analysis in Microelectronics

Hollerith, C. (Speaker)¹; Pressel, K.²

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Oral-Poster-Presentation

A new approach of training a deep learning algorithm for phase segmentation of steel microstructures

Chaurasia, N. (Speaker)¹; Jha, S.K.¹; Sangal, S.¹

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

Harnessing Machine Learning for Process Optimization in Lead-Based Electroceramics

Bayir, M.C. (Speaker)¹; Temizel, R.C.²; Mensur, E.¹

Plenary Lecture

Dahmen, T. (Speaker)¹

Conference on Artificial Intelligence in Materials Science and Engineering - AI MSE 2023

© 2025