Machine learning in industrial X-ray computed tomography–a review
S Bellens, P Guerrero, P Vandewalle… - CIRP Journal of …, 2024 - Elsevier
X-ray computed tomography (XCT) has been shown to be a reliable tool for quality
inspection, material evaluation, and dimensional measurement tasks across diverse …
inspection, material evaluation, and dimensional measurement tasks across diverse …
[HTML][HTML] Comprehensive analysis of heavy metal soil contamination in mining Environments: Impacts, monitoring Techniques, and remediation strategies
A Haghighizadeh, O Rajabi, A Nezarat… - Arabian Journal of …, 2024 - Elsevier
Soil contamination by lead, zinc, iron, manganese, and copper is a widespread
environmental issue associated with the mining industry. Primary sources include mining …
environmental issue associated with the mining industry. Primary sources include mining …
Overcoming stereological Bias: A workflow for 3D mineral characterization of particles using X-ray micro-computed tomography
Mineral separation processes operate on properties of individual particle, which can
currently be quantified with 2D characterization techniques, namely 2D automated …
currently be quantified with 2D characterization techniques, namely 2D automated …
[HTML][HTML] Three-dimensional characterization of porosity in iron ore pellets: A comprehensive study
This paper presents a comprehensive study on the production and reduction of high-quality
iron ore pellets characterized by a basicity index nearing 0.5 and diameters ranging from 1 …
iron ore pellets characterized by a basicity index nearing 0.5 and diameters ranging from 1 …
[HTML][HTML] Quantitative 3D characterization of chromite ore particles
JRA Godinho, S Gupta, CG da Silva Tochtrop… - Minerals …, 2023 - Elsevier
The main techniques used to characterize raw materials are currently bulk or 2D. This is a
consequence of the current lack of standardized and automated methods to characterize …
consequence of the current lack of standardized and automated methods to characterize …
Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry
Central to the digital transformation of the process industry are Digital Twins (DTs), virtual
replicas of physical manufacturing systems that combine sensor data with sophisticated data …
replicas of physical manufacturing systems that combine sensor data with sophisticated data …
Machine learning for open-pit mining: a systematic review
Nowadays, open-pit mining is the large-scale extraction of valuable ore materials from the
surface with the use of modern mining equipment. If not operated properly, various …
surface with the use of modern mining equipment. If not operated properly, various …
Analysis of Microscopic Remaining Oil Based on the Fluorescence Image and Deep Learning
Y Zhang, C Lin, L Ren - Journal of Fluorescence, 2024 - Springer
Fossil fuels like oil and natural gas continue to be the primary sources of global energy.
Enhancing hydrocarbon recovery from exploited reservoirs has been a major scientific …
Enhancing hydrocarbon recovery from exploited reservoirs has been a major scientific …
Recent advances in machine learning algorithms for sintering processes
S Azizi - Synthesis and Sintering, 2023 - synsint.com
Abstract Machine learning (ML) is a fast-growing field that has vast applications in different
areas and sintering has had no exemption from that. In this paper, the application of ML …
areas and sintering has had no exemption from that. In this paper, the application of ML …
ParticleSeg3D: A scalable out-of-the-box deep learning segmentation solution for individual particle characterization from micro CT images in mineral processing and …
Minerals, metals, and plastics are indispensable for a modern society. Yet, their limited
supply necessitates optimized extraction and recycling processes, which must be …
supply necessitates optimized extraction and recycling processes, which must be …