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 …

[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 …

Overcoming stereological Bias: A workflow for 3D mineral characterization of particles using X-ray micro-computed tomography

A Siddique, JRA Godinho, J Sittner, L Pereira - Minerals Engineering, 2023 - Elsevier
Mineral separation processes operate on properties of individual particle, which can
currently be quantified with 2D characterization techniques, namely 2D automated …

[HTML][HTML] Three-dimensional characterization of porosity in iron ore pellets: A comprehensive study

P Cavaliere, B Sadeghi, L Dijon, A Laska… - Minerals …, 2024 - Elsevier
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 …

[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 …

Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry

M Mayr, GC Chasparis, J Küng - … Conference on Big Data Analytics and …, 2024 - Springer
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 …

Machine learning for open-pit mining: a systematic review

SQ Liu, L Liu, E Kozan, P Corry, M Masoud… - … Journal of Mining …, 2025 - Taylor & Francis
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 …

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 …

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 …

ParticleSeg3D: A scalable out-of-the-box deep learning segmentation solution for individual particle characterization from micro CT images in mineral processing and …

K Gotkowski, S Gupta, JRA Godinho, CGS Tochtrop… - Powder Technology, 2024 - Elsevier
Minerals, metals, and plastics are indispensable for a modern society. Yet, their limited
supply necessitates optimized extraction and recycling processes, which must be …