Optimisation of Operator Support Systems through Artificial Intelligence for the Cast Steel Industry: A Case for Optimisation of the Oxygen Blowing Process Based on Machine Learning Algorithms

Article Chemistry, Multidisciplinary

Fake It Till You Make It: Guidelines for Effective Synthetic Data Generation

Fida K. Dankar et al.

Summary: Synthetic data provides a privacy-protecting mechanism for healthcare data, generating artificial datasets without identifiable information for safe sharing. The paper evaluates the impact of different synthetic data generation and usage settings on the utility of the data and models, aiming to provide insights into the best practices when working with synthetic data.

APPLIED SCIENCES-BASEL (2021)

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Article Metallurgy & Metallurgical Engineering

Optimization of Dephosphorization Parameter in Consteel Electric Arc Furnace Using Rule Set Model

Chao Chen et al.

Summary: This article presents a rule set model combining a k-means method and a decision tree model to optimize the dephosphorization process by extracting rule set from actual production data.

STEEL RESEARCH INTERNATIONAL (2021)

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Article Materials Science, Multidisciplinary

Machine Learning Methods for the Prediction of the Inclusion Content of Clean Steel Fabricated by Electric Arc Furnace and Rolling

Estela Ruiz et al.

Summary: Machine learning classification models were used to analyze experimental data of clean cold forming steel, identifying variables influencing inclusion content and interpreting their impact through Permutation Importance and Partial Dependence Plots. The study found that changes induced by hot rolling in coil diameter and other metallurgical operations significantly affect inclusion cleanliness, and recommendations were made to optimize sampling processes and manufacturing conditions to improve steel inclusion cleanliness.

METALS (2021)

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Review Computer Science, Artificial Intelligence