Toward learning steelmaking—A review on machine learning for basic oxygen furnace process
MK Ghalati, J Zhang, G El‐Fallah… - Materials Genome …, 2023 - Wiley Online Library
Basic oxygen furnace (BOF) steelmaking is the most widely used process in global steel
production today, accounting for around 70% of the industry's output. Due to the physical …
production today, accounting for around 70% of the industry's output. Due to the physical …
Anomaly Detection in Industrial Machinery Using IoT Devices and Machine Learning: A Systematic Mapping
SF Chevtchenko, EDS Rocha, MCM Dos Santos… - IEEE …, 2023 - ieeexplore.ieee.org
Anomaly detection is critical in the smart industry for preventing equipment failure, reducing
downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large …
downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large …
Soft Computing Application in Mining, Mineral Processing and Metallurgy with an Approach to Using It in Mineral Waste Disposal
N Herrera, M Sinche Gonzalez, J Okkonen… - Minerals, 2023 - mdpi.com
In the past two decades, the mining sector has increasingly embraced simulation and
modelling techniques for decision-making processes. This adoption has facilitated …
modelling techniques for decision-making processes. This adoption has facilitated …
Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: Enabling Distributed High-Temperature Measurements and Strain Monitoring in Steelmaking and …
This study demonstrates the use of fiber Bragg grating (FBG) sensors for distributed
temperature and strain monitoring in steelmaking and foundry applications. Integrated into …
temperature and strain monitoring in steelmaking and foundry applications. Integrated into …
[HTML][HTML] An unsupervised end-to-end approach to fault detection in delta 3D printers using deep support vector data description
Fault detection in 3D printers is crucial for safety and quality assurance, emphasizing
proactive prediction over reactive rectification based on manufacturing factors. Presently …
proactive prediction over reactive rectification based on manufacturing factors. Presently …
Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing
Multi-channel profile data analysis is an important research topic in modern quality
management for advanced manufacturing. The most crucial part is how to model the profile …
management for advanced manufacturing. The most crucial part is how to model the profile …
Profile extraction and defect detection for stereolithography curing process based on multi-regularized tensor decomposition
Optical lenses cured from the stereolithography process are still at their primitive stage,
where the detection of process faults and product defects is of great importance. Such …
where the detection of process faults and product defects is of great importance. Such …
New green and low-carbon technology for all-sensible heat recovery of converter gas
J Zhao, B Li, X Wei, T Li, S Li - Journal of Cleaner Production, 2024 - Elsevier
The smelting process of converter determines the explosive, dusty and intermittent nature of
gas itself. Therefore, either the way of water (oxygen converter gas recovery system) or mist …
gas itself. Therefore, either the way of water (oxygen converter gas recovery system) or mist …
A metallurgical dynamics-based method for production state characterization and end-point time prediction of basic oxygen furnace steelmaking
Q Qian, Q Dong, J Xu, W Zhao, M Li - Metals, 2022 - mdpi.com
Basic Oxygen Furnace (BOF) steelmaking is an important way for steel production. Correctly
recognizing different blowing periods and abnormal refining states is significant to ensure …
recognizing different blowing periods and abnormal refining states is significant to ensure …
Monitoring and diagnosis of complex production process based on free energy of Gaussian–Bernoulli restricted Boltzmann machine
Q Dong, Q Qian, M Li, G Xu - Journal of Iron and Steel Research …, 2023 - Springer
Online monitoring and diagnosis of production processes face great challenges due to the
nonlinearity and multivariate of complex industrial processes. Traditional process monitoring …
nonlinearity and multivariate of complex industrial processes. Traditional process monitoring …