Equipment size effects on open pit mining performance

Bozorgebrahimi, A; Hall, R.; Morin, MA

doi:10.1080/13895260412331326821

Cited by 29 publications

(13 citation statements)

References 1 publication

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“…The reduction in berm widths intensifies rockfall problems, and will also increase instability problems on a bench and inter-ramp scale. Decrease in the ramp widths will cause safety problems for trucks on the ramps, which can lead to a requirement for smaller units (Bozorgebrahimi, Hall, and Morin, 2005). Finally, an increase in the BSA could increase safety concerns for the operation.…”

Section: Governing Risk Elements Through Open Pit Slope Optimizationmentioning

confidence: 99%

Governing risk elements through open pit slope optimization

Golestanifar

Ahangari

Goshtasbi

et al. 2018

J. South. Afr. Inst. Min. Metall.

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With the increasing competition in global mineral markets, designers are attempting to drive down overall mining costs. The demands for steeper pit slopes have triggered developments in the field of modern and comprehensive slope design. Risk-based optimization techniques are one of the most challenging state-of-the-art solutions for enhancing conventional procedures. Recognizing risk aspects has a fundamental role in updating the methods. Considering geotechnical and mine planning issues, this study describes the consequences of varying slope angles on final pit walls. Twenty-three risk elements are introduced and discussed in four groups: economic, technical, strategic, and regulatory compliance. Related examples are given on the state of the elements, and possible ways to achieve them from overall slope optimization studies of the Sungun copper mine in Iran. The circumstances indicate that decisions on optimized slopes do not relate only to geotechnical studies, but that relevant consequences depend on the four groups. Evaluation of the elements can promote slope optimization based on the concepts of risk. pit slope design, risk evaluation, slope stability, mine planning, Sungun copper mine.

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Section: Governing Risk Elements Through Open Pit Slope Optimizationmentioning

confidence: 99%

Governing risk elements through open pit slope optimization

Golestanifar

Ahangari

Goshtasbi

et al. 2018

J. South. Afr. Inst. Min. Metall.

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“…Finding the correct SMU size is a matter of trial and error, and should focus on attempting to find the smallest possible regularized size that will replicate the ore and its grade distribution of the deposit (Kumral 2015). The clustering size is reflective of the equipment used; each shovel has a certain boom length and bucket size (Bozorgebrahimi et al 2005). These two parameters with the class of shovel (i.e., retro, frontal, hydraulic, line, and electro-hydraulic), will define the working size that a shovel must have to operate at capacity.…”

Section: Introductionmentioning

confidence: 99%

“…Dilution is considered regarding the bench height; however, no analysis is carried out to define the impact of equipment size on the generation of dig-limits. Bozorgebrahimi et al (2003) generated this limits using a methodology such as best destination, reblocked the initial deposit into larger SMUs based upon the equipment used (Samanta et al 2002;Bozorgebrahimi et al 2005), and studied the parameters affecting equipment sizing extensively. These parameters are summarized in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

A Practical Approach to Mine Equipment Sizing in Relation to Dig-Limit Optimization in Complex Orebodies: Multi-Rock Type, Multi-Process, and Multi-Metal Case

Ruiseco

Kumral

2016

Nat Resour Res

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Equipment sizing is a developed field of mining engineering, which considers all aspects related to productivity, and grade distribution. Current methods of equipment sizing consider block dilution, but do not analyze the impact of the selectivity changes on practical diglimits. This research analyzed the impact of varying equipment sizes on a highly variable three destination, Au and Cu bench, in a sulfide/oxide deposit. The study shows that selectivity sizing profit and size relationships are nonlinear, and exhibit severe break points if insufficiently selective equipment is used. The proposed technique can be used for sizing mine equipment in complex deposits.

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“…The design, geometry and scheduling of an open pit mine has significant influence on the performance and utilisation of all mine machinery deployed within the pit (Ritter, 2016b;Thompson, 2005). Similarly, the sizing and capacities are key consideration for determining the layout and geometry of an open pit (Bozorgebrahimi et al, 2005;Bozorgebrahimi et al, 2003;Radlowski, 1988 Two schools of thought emerge on the impact of mine design and planning on viability of FMIPCC from the literature review. One view suggests that the FMIPCC is unviable due to inflexibility of the current paradigm of mine design and planning methods which often leads to sub-optimal performance (Morrison, 2017;Tutton and Streck, 2009).…”

Section: Mine Design Layout Planning and Schedulingmentioning

confidence: 99%

“…Similar to observations made in previous sections of this chapter, a critical review of IPCC literature shows limited coverage of system performance, productivity and utilisation of FMIPCC systems. Tynan (2016b) 5 5 5 Khorzoughi and Hall (2016) 3 3 Mohammadi et al (2015) 3 3 Arputharaj (2015a); Arputharaj (2015b) 3 3 Kalra et al (2015) 5 5 Kansake and Suglo (2015) 5 Sarkhel and Dey (2015) 5 5 Lumley and McKee (2014) 5 5 5 Lanke et al (2014) 5 5 Rodovalho and Cabral (2014) 5 Mahdi and Morteza (2014) 5 5 Ritter et al (2014) 2 2 Adadzi (2013) 5 Yilmaz (2014) 2 2 Steven (2012) 2 Choudaha et al (2012) 2 2 Zammori et al (2011) 5 5 Elevli and Elevli (2010) 5 Morriss (2008) 1 1 Muchiri and Pintelon (2008) 5 5 Callow (2006) 5 De Ron and Rooda (2006) 5 Singh and Narendrula (2006) 5 Paraszczak (2005) 5 Siegrist and Morris (2005) 5 5 5 Bozorgebrahimi et al (2005) 5 5 Workman- Davies and Van Loggerenberg (2003) 5 5 5 Gurgenci et al (2002) 5 Lukacs (2001) 5 Radlowski (1988) 2 2 Sense and Pfleider (1968) 5 5 Sense (1964) 5…”

Section: System Performance Productivity and Utilisationmentioning

confidence: 99%

Time utilisation modelling of fully mobile in-pit crushing and conveying systems

Dzakpata¹

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A comprehensive review of literature published during the last two decades shows that Fullymobile In-pit Crushing and Conveying systems (FMIPCC) systems in surface mines have been increasingly studied by the mining industry and have been adopted more often by mines having tabular deposits. In Australia, the majority of FMIPCC implementations have failed to address persistent problems of overestimation of FMIPCC efficiency over the past few decades, leading to low confidence in the uptake of the system. Additionally, current time utilisation models predict single-point values and do not account for the dynamic relationship with the variability of key mine design inputs (including bench width, bench height and bench length) on system utilisation. This research focuses on investigating the influence of key mine design variables (geometry approaches, sequencing and scheduling) on the performance of FMIPCC systems in open pit and open cut applications. The methodology used in this research first establishes the relationship between key mine design variables and FMIPCC performance and then develops a novel approach for predicting FMIPCC utilisation using stochastic variables derived from historic operational data. This research further investigates of the impact of open pit exploitation schemes on FMIPCC utilisations using a case study typical of Australian coal mining. The study result predicts FMIPCC operating time ranging from 3,379 -5,233 hours and 4,347 -4,963 hours based on a confidence interval (CI) of 95% and 50% respectively. The novel contributions of this research include the development of an improved stochastic approach to time utilisation modelling of FMIPCC systems. The potential exists to extend its use to other alternative continuous haulage systems remains. Additionally, this is the first work to comprehensively evaluate the effects of mine planning variables on the overall effective utilisation of FMIPCC systems. A comprehensive historical equipment performance data set is used to document system performance ranges along with simple statistical distributions. Finally, the research has developed the first stochastic tool for modelling the utilisation of FMIPCC, considering variability of the key modelling inputs. This research successfully fulfilled its objectives by providing evidence to support the hypothesis that a source of underperformance is linked to overestimation of productive hours and throughput of FMIPCC systems. Future work should extend this research work to investigate the application of FMIPCC beyond in-pit material handling, including ex-pit environment and integrated study of multiple open pits.

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Equipment size effects on open pit mining performance

Cited by 29 publications

References 1 publication

Governing risk elements through open pit slope optimization

Governing risk elements through open pit slope optimization

A Practical Approach to Mine Equipment Sizing in Relation to Dig-Limit Optimization in Complex Orebodies: Multi-Rock Type, Multi-Process, and Multi-Metal Case

Time utilisation modelling of fully mobile in-pit crushing and conveying systems

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