scholarly journals A Review of Alternative Procedures to the Bond Ball Mill Standard Grindability Test

Metals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1114
Author(s):  
Vladimir Nikolić ◽  
Gloria G. García ◽  
Alfredo L. Coello-Velázquez ◽  
Juan M. Menéndez-Aguado ◽  
Milan Trumić ◽  
...  

Over the years, alternative procedures to the Bond grindability test have been proposed aiming to avoid the need for the standard mill or to reduce and simplify the grinding procedure. Some of them use the standard mill, while others are based on a non-standard mill or computation techniques. Therefore, papers targeting to propose a better alternative claim to improve validity, to reduce test duration, or to propose simpler and faster alternative methods for determining the Bond work index (wi). In this review paper, a compilation and critical analysis of selected proposals is performed, concluding that some of the short procedures could be useful for control purposes, while the simulation-based procedures could be interesting within a process digitalisation strategy.

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1606
Author(s):  
Gloria González García ◽  
Alfredo L. Coello-Velázquez ◽  
Begoña Fernández Pérez ◽  
Juan M. Menéndez-Aguado

There is no doubt about the practical interest of Fred Bond’s methodology in the field of comminution, not only in tumbling mills design and operation but also in mineral raw materials grindability characterization. Increasing energy efficiency in comminution operations globally is considered a significant challenge involving several Sustainable Development Goals (SDGs). In particular, the Bond work index (wi) is considered a critical parameter at an industrial scale, provided that power consumption in comminution operations accounts for up to 40% of operational costs. Despite this, the variability of wi when performing the ball mill Bond’s standard test is not always understood enough. This study shows the results of a variability analysis (a 33 factorial design) performed to elucidate the influence on wi of several parameters obtained from the particle size distribution (PSD) in feed and product. Results showed a clear variability in the work and grindability indexes with some of the variables considered.


Metals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1079
Author(s):  
Victor Ciribeni ◽  
Juan M. Menéndez-Aguado ◽  
Regina Bertero ◽  
Andrea Tello ◽  
Enzo Avellá ◽  
...  

As a continuation of a previous research work carried out to estimate the Bond work index (wi) by using a simulator based on the cumulative kinetic model (CKM), a deeper analysis was carried out to determine the link between the kinetic and energy parameters in the case of metalliferous and non-metallic ore samples. The results evidenced a relationship between the CKM kinetic parameter k and the grindability index gbp; and also with the wi, obtained following the standard procedure. An excellent correlation was obtained in both cases, posing the definition of alternative work index estimation tests with the advantages of more straightforward and quicker laboratory procedures.


2018 ◽  
Vol 115 (5) ◽  
pp. 508 ◽  
Author(s):  
Cemaliye Seflek ◽  
Oktay Bayat

This experimental work aims at studying the effect of particle size on the microwave pre-treatment for the grindability of Bolkardag (Nigde, Turkey) gold ore for cyanide leaching. Three different particle size batches (−8 + 4.7 mm, −4.75 + 2 mm and −2 + 1 mm) were used for microwave treatment. Each sub-samples were exposed to four different power levels of microwave energy (0.09, 0.18, 0.36 and 0.6 kW) at exposure times of 5, 10, 15 and 30 minutes and then grindability characteristic of the treated samples were investigated with Berry and Bruce comparative grindability method. It was clearly seen that increasing power level and exposure time caused a reduction in comparative Bond Work index. A maximum reduction in Bond Work index (73.54%) was achieved by 0.6 kW at 30 minutes of microwave treatment. Compared to the untreated sample’s results, gold and silver extraction rates increased, using microwave-treated samples, about 7% and 9% after 77 hours cyanide leaching, respectively. Additionally, the hydrated lime added samples (after 0.6 kW at 30 minutes of microwave treatment) were used in the cyanide leaching tests to determine the possible effect. It was observed that there was no significant difference on leaching extraction rates using lime free or lime added samples. Applying microwave pre-treatment before cyanide leaching, the gold and silver extraction rates could be increased and also the cost of communition could be reduced due to easier breakage of the ore due to a significant decrease in Bond Work index.


2018 ◽  
Vol 25 (4) ◽  
pp. 795-804
Author(s):  
Hossein Inanloo Arabi Shad ◽  
F Sereshki ◽  
M Ataei ◽  
M Karamoozian

2013 ◽  
Vol 123 ◽  
pp. 78-86 ◽  
Author(s):  
Barnabás Csőke ◽  
Ádám Rácz ◽  
Gábor Mucsi

Author(s):  
Baijnath Kaushik ◽  
◽  
Navdeep Kaur ◽  
Amit Kumar Kohli ◽  
◽  
...  

The objective of this paper is to present a novelmethod for achievingmaximumreliability in fault-tolerant optimal network design when networks have variable size. Reliability calculation is a most important and critical component when fault-tolerant optimal network design is required. A network must be supplied with certain parameters that guarantee proper functionality and maintainability in worse-case situations. Many alternative methods for measuring reliability have been stated in the literature for optimal network design. Most of these methods, mentioned in the literature for evaluating reliability, may be analytical and simulation-based. These methods provide significant ways for computing reliability when a network has a limited size. Significant computational effort is also required for growing variable-sized networks. A novel neural network method is therefore presented to achieve significant high reliability in fault-tolerant optimal network design in highly growing variable networks. This paper compares simulation-based analytical methods with improved learning rate gradient descent-based neural network methods. Results show that improved optimal network design with maximum reliability is achievable by a novel neural network at a manageable computational cost.


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