Challenges in Raw Material Treatment at the Mechanical Processing Stage

Saramak, D.

doi:10.3390/min11090940

Cited by 7 publications

(5 citation statements)

References 34 publications

(33 reference statements)

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“…However, as previously discussed, the roller crushing process (i.e., size reduction to −2.8 mm) has proven sufficient for chlorine compound liberation, allowing the achievement of leaching levels similar to those of ball-milled samples (−0.5 mm slag). This implies that no further comminution is required after crushing to −2.8 mm, thus eliminating the well-known costs related to grinding [25]. This evidence is also comparable to those by Davies et al [19] and Bruckard and Woodcock [17], which find water leaching to be efficient for −2 mm aluminum salt slags.…”

Section: Leaching Resultssupporting

confidence: 82%

Optimization of Water Leaching of Chlorides from Aluminum Salt Slag

et al. 2022

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Aluminum recycling generates large amounts of hazardous wastes, known as salt slags, consisting mainly of oxides, metallic aluminum, and salt fluxes. Water leaching is a common technique used for salt removal, being a decisive operation due to water usage and the need to achieve sufficient salt recovery. In this study, water leaching tests under varied operational conditions (water type, slag particle size, solid content, and leaching time) were carried out in salt slag samples obtained from a Brazilian aluminum scrap melting company. Leaching efficiency was assessed by the % chlorine leached. The optimal leaching condition, defined as the one that resulted in the highest chloride removal from the slag together with appropriate operational conditions (larger viable slag size, lower leaching time, etc.), was identified for a slag size below 2.8 mm, 30 wt% of solids in pulp, and a leaching time of 90 min. The results showed that it was possible to recover more than 92% of the salts initially contained in the raw slag, resulting in a leached material with less than 2.5% salts. The recovered salt characteristics showed potential for recycling and could be re-mixed to the salt flux used for aluminum melting. The possibility of achieving higher efficiencies and lower water consumption during leaching was also discussed, as was a preliminary flowsheet for salt slag treatment.

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Section: Leaching Resultssupporting

confidence: 82%

Optimization of Water Leaching of Chlorides from Aluminum Salt Slag

et al. 2022

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“…Mineral processing modeling is often a difficult task due to the multiple variables involved and the complex dynamics that comprise the value chain. Despite its complexity and the application of many physical, mechanical, chemical, and other types separation processes and operations, mineral processing can generally be divided into a reduction in the size of the feed material and a separation of useful minerals from the gangue [124]. As part of the physical treatment (a reduction in ROM), grinding is the most relevant sub-process since it is the one that consumes more resources as a result of the reduction in the particle size in large rotating equipment (such as SAG mills).…”

Section: Discussionmentioning

confidence: 99%

“…To overcome these defects, the algorithm employs two techniques: weighted quantile sketching and scatter-conscious divisions. The algorithm also uses second-order gradients (Newton boosting) to converge faster and advance regularization, improving the model's generalizability and overcoming overfitting problems in terms of an increasing gradient [124].…”

Section: Validation Of ML Algorithmsmentioning

confidence: 99%

Optimization of the SAG Grinding Process Using Statistical Analysis and Machine Learning: A Case Study of the Chilean Copper Mining Industry

et al. 2023

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Considering the continuous increase in production costs and resource optimization, more than a strategic objective has become imperative in the copper mining industry. In the search to improve the efficiency in the use of resources, the present work develops models of a semi-autogenous grinding (SAG) mill using statistical analysis and machine learning (ML) techniques (regression, decision trees, and artificial neural networks). The hypotheses studied aim to improve the process’s productive indicators, such as production and energy consumption. The simulation of the digital model captures an increase in production of 4.42% as a function of mineral fragmentation, while there is potential to increase production by decreasing the mill rotational speed, which has a decrease in energy consumption of 7.62% for all linear age configurations. Considering the performance of machine learning in the adjustment of complex models such as SAG grinding, the application of these tools in the mineral processing industry has the potential to increase the efficiency of these processes, either by improving production indicators or by saving energy consumption. Finally, the incorporation of these techniques in the aggregate management of processes such as the Mine to Mill paradigm, or the development of models that consider the uncertainty of the explanatory variables, could further increase the performance of productive indicators at the industrial scale.

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“…Low-grade ore processing requires new technologies and economic models. In particular, selecting adequate processing technologies is crucial for the economic and sustainable production of metals and non-metals, as the stage of ore processing influences the quality of the final product [5,6].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Ni-Cu Ore from Zapolyarnoe Based on Mineralogical and Physical Properties before and after Comminution

Bravo,

Lieberwirth,

Popov

2024

Minerals

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For the effective comminution and subsequent enrichment of mineral ores, comprehensive knowledge of their mineralogical and physical properties is required. Using an integrated methodology, this study evaluated samples of polymetallic Ni-Cu ore from Zapolyarnoe, Russia. Several analytical techniques were utilised, including optical microscopy, microindentation with Vickers geometry, the Point Load Test, and Mineral Liberation Analysis (MLA). The purpose of this study was to determine mineral associations, physical features, and enrichment during jaw crusher comminution. The acquired properties included the Point Load Strength Index, Vickers Hardness Number, and fracture toughness. The MLA method characterised seven fractions in terms of particle size distribution, degree of liberation, association, and modal mineralogy. Magnetite, pyrrhotite, pentlandite, and chalcopyrite were calculated in terms of wt% and their textural features. The enrichment of each ore phase in fractions with particle sizes smaller than 400 µm was determined. The influence of this enrichment was discovered to be correlated with various textural and structural parameters, such as intergrowth, grain size, and crack morphologies after indentations. In addition, the chromium content of magnetite contributed to an increase in the fracture toughness values. Despite the complexities involved, even limited samples of materials provide valuable insights into processing behaviour, emphasising the importance of considering mineralogical parameters in comminution studies.

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Challenges in Raw Material Treatment at the Mechanical Processing Stage

Cited by 7 publications

References 34 publications

Optimization of Water Leaching of Chlorides from Aluminum Salt Slag

Optimization of Water Leaching of Chlorides from Aluminum Salt Slag

Optimization of the SAG Grinding Process Using Statistical Analysis and Machine Learning: A Case Study of the Chilean Copper Mining Industry

Evaluation of Ni-Cu Ore from Zapolyarnoe Based on Mineralogical and Physical Properties before and after Comminution

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