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RESEARCH PAPER · Journal of Iron and Steel Research International · 2024

Machine learning-based performance predictions for steels considering manufacturing process parameters: a review

Wei Fang, Jiaxin Huang, Tiexu Peng, Yang Long, Fuxing Yin

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42 direct citing works

Machine learning-based performance predictions for steels considering manufacturing process parameters: a reviewOriginalMachine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design10Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures7Comprehensive Evaluation, Prediction, and Optimization of Sintering State2Rapid damage assessment and rotation angle model of EEP-HSSBC connections under post-fire earthquake using machine learning1Recent Innovations in Computer and Automation Engineering for Performance Improvement in the Steel Industry Production Chain: A Review6Mechanical Property Prediction of Industrial Low-Carbon Hot-Rolled Steels Using Artificial Neural Networks9Iron-Based High-Temperature Alloys: Alloying Strategies and New Opportunities19Raw materials consumption reduction for practical electric arc furnace steelmaking: a data association rules mining approach with improved evaluation indicator3Elman Network Classifier Based on Hyperactivity Rat Swarm Optimizer and Its Applications for AlSi10Mg Process Classification0A Comprehensive Study on Fatigue Strength Prediction of a Broad Range of Steels Using Machine Learning2Machine Learning Applications in Predicting Friction Properties of Bearing Steel: A Review0A data-driven integrated framework for collaborative prediction and optimisation of hot-rolled steel strip shape0Predictive modeling for mechanical properties of cold-rolled strip steel based on random forest regression and whale optimization algorithm0Metallurgy‐Guided Process Window Optimization and Stability Analysis for Customized Hot‐Rolled Steel Production0Steel microstructure analysis using transfer learning: a study on data leakage1Development of a hot processing map by PM-MGDD model and microstructural characterization of GH3044 alloy0Application of machine learning models in continuous casting process0Analytical model of force and deformation parameters in TRB upward-rolling0Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review1Room-temperature-property anchoring for family-transfer prediction of high-temperature properties in low-alloy steels0Data-Driven Framework for Anomaly Identification and Process Optimization in Continuous Casting0Domain-Knowledge-Guided Feature Engineering for Small-Sample Machine Learning Prediction of Mechanical Properties in Low-Carbon Hot-Rolled Steel Strips0Machine Learning for Structural Steels: Materials Design, Property Prediction, Durability, and Future Directions0Enhancement of forming tool performance through combined macro-geometric optimization and regional micro-scale passivation0Prediction of Mechanical Properties of Large-Scale Medium-Carbon Cast Steel Components Based on Machine Learning0Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel0

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26 direct citing papers saved.

  1. Machine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design

    Materials & Design · 2024-11-09

    Bin Zhu, Nathanael Leung, Brandon Steel, David England, He Yinglong, Andrew J. London, Hannah Zhang, Michael J. Gorley, Yiqiang Wang, Mark J. Whiting, Tan Sui

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  2. Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures

    Technologies · 2025-02-11

    Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emílio Marengo

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  3. Comprehensive Evaluation, Prediction, and Optimization of Sintering State

    Metallurgical and Materials Transactions B · 2025-02-19

    Mingyu Wang, Mansheng Chu, Jue Tang, Quan Shi, Zhen Zhang, Zhifeng Zhang

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  4. Rapid damage assessment and rotation angle model of EEP-HSSBC connections under post-fire earthquake using machine learning

    Engineering Structures · 2025-03-24

    Jixiang Xu, Yifan Zhang, Jianping Han

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  5. Recent Innovations in Computer and Automation Engineering for Performance Improvement in the Steel Industry Production Chain: A Review

    Energies · 2025-04-12

    Crescenzo Pepe, Giorgia Farella, Giovanni Bartucci, Silvia Maria Zanoli

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  6. Mechanical Property Prediction of Industrial Low-Carbon Hot-Rolled Steels Using Artificial Neural Networks

    Materials · 2025-06-23

    Saurabh Tiwari, Hyoju Ahn, Maddika Harinatha Reddy, Nokeun Park, N.S. Reddy

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  7. Iron-Based High-Temperature Alloys: Alloying Strategies and New Opportunities

    Materials · 2025-06-24

    Yingjie Qiao, Yu Ni, Kun Yang, Peng Wang, Xiaodong Wang, Ruiliang Liu, Bin Sun, Chengying Bai

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  8. Raw materials consumption reduction for practical electric arc furnace steelmaking: a data association rules mining approach with improved evaluation indicator

    Journal of Iron and Steel Research International · 2025-06-29

    Yuchi Zou, Lingzhi Yang, Hang Hu, Guannan Li, Feng Zeng, Shuai Wang, Feng Chen, Yufeng Guo

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  9. Elman Network Classifier Based on Hyperactivity Rat Swarm Optimizer and Its Applications for AlSi10Mg Process Classification

    Processes · 2025-09-01

    Rui Ni, Hanning Chen, Xiaodan Liang, Maowei He, Yelin Xia, Liling Sun

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  10. A Comprehensive Study on Fatigue Strength Prediction of a Broad Range of Steels Using Machine Learning

    Journal of Materials Engineering and Performance · 2025-09-15

    Mohammed Shahbaz Quraishy, Tarun Kumar Kundu

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  11. Machine Learning Applications in Predicting Friction Properties of Bearing Steel: A Review

    ACS Materials Letters · 2025-12-31

    X. Wang, Tingting Shi, Lijuan Cheng, Wenqi Zhao, Suwen Hu, Li Fu Cui, Peter Kaehuei Liaw

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  12. A data-driven integrated framework for collaborative prediction and optimisation of hot-rolled steel strip shape

    International Journal of Production Research · 2026-02-01

    Jie Dong, Xu-yan Yang, Qing-quan Xu, Silvio Simani, Peng Kai-xiang

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  13. Predictive modeling for mechanical properties of cold-rolled strip steel based on random forest regression and whale optimization algorithm

    Journal of Iron and Steel Research International · 2026-02-07

    Hong-Lei Cai, Yi-Ming Fang, Le Liu, Li-Hui Ren, Zhendong Liu, Xiaodong Zhao

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  14. Metallurgy‐Guided Process Window Optimization and Stability Analysis for Customized Hot‐Rolled Steel Production

    steel research international · 2026-02-09

    Pengju Xu, Yifan Yan, Ri Xue Jin, Zhimin Lv, Zhiyan Zhang, Yiquan An, Ziqing Zhu, Xiangyu Cao

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  15. Steel microstructure analysis using transfer learning: a study on data leakage

    Journal of Materials Science · 2026-04-04

    Marcel Wentzien, Jerome Ingber, Jörg Schlötterer, Thomas Friedrich, Henning Kempka, Dirk Schmalzried, Maik Kunert

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  16. Development of a hot processing map by PM-MGDD model and microstructural characterization of GH3044 alloy

    Archives of Civil and Mechanical Engineering · 2026-04-14

    Yuanming Liu, Fang Huang, Xilong Hu, Z H Wang, Wangzhe Du, Jian Shao, Laishan Yang

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  17. Application of machine learning models in continuous casting process

    Journal of Iron and Steel Research International · 2026-05-09

    Yi Ji, Jia-Xi Chen, Lejun Zhou, Wan-Lin Wang, Si-Bao Zeng, Zhang Li-wu, Hong-Liang Lin, Xiao-Kang Liu, Jiang-hua Qi, Kui Chen

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  18. Analytical model of force and deformation parameters in TRB upward-rolling

    Journal of Iron and Steel Research International · 2026-05-14

    Yuan-Ming Liu, Xiang Huang Cheng, Yi-Zhong Cao, LI Shuang-Chi, Ya-xing Liu, Yu Huang, Rong-sheng Sun, Dong-Ping He

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  19. Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review

    Next Materials · 2026-06-25

    Mohsen Soori, Behrooz Arezoo B

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  20. Room-temperature-property anchoring for family-transfer prediction of high-temperature properties in low-alloy steels

    Materials Letters · 2026-07-20

    Chengrong Xie, Dong Chen, W J Zhao, Z Zhang, Z.G. Li, Jian Kang, Guo Ding Yuan

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  21. Data-Driven Framework for Anomaly Identification and Process Optimization in Continuous Casting

    Metallurgical and Materials Transactions B · 2026-07-31

    Xinyu Ning, Jiyang Zhang, Haijun Li, Yanfeng Zhang, Guodong Wang

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  22. Domain-Knowledge-Guided Feature Engineering for Small-Sample Machine Learning Prediction of Mechanical Properties in Low-Carbon Hot-Rolled Steel Strips

    Metals · 2026-08-21

    Saurabh Tiwari, Hyoju Ahn, Jongwon Lee, Nokeun Park

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  23. Machine Learning for Structural Steels: Materials Design, Property Prediction, Durability, and Future Directions

    Materials · 2026-08-25

    Guomin Wei, Minghe Li, Bo Cui, Wencui Xiu, Asmawan Mohd Sarman

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  24. Enhancement of forming tool performance through combined macro-geometric optimization and regional micro-scale passivation

    Journal of Materials Research and Technology · 2026-09-11

    Xi Chen, Yuyang Wu, Jiaqiang Dang, Qi Wang, Qinglong An, Ming Chen, Hun Guo, Hao Zheng, Wenzhuang Lu, Yanyan Yan

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  25. Prediction of Mechanical Properties of Large-Scale Medium-Carbon Cast Steel Components Based on Machine Learning

    International Journal of Metalcasting · 2026-09-29

    Kai Cheng, Feng Mao, Xingfu Wang, Yi Zhong, Ruxing Shi, 林乙丑, Litao Yin, Baoning Yu, Liujie Xu, Chong Chen, Kunming Pan, Shizhong Wei

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  26. Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel

    Journal of Materials Informatics · 2026-09-30

    Juan Yang, Wentao Zhao, Bolin Lu, Wangzhong Mu, Xiaoxu Huang, Ziyong Hou

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