A Study of Digging Productivity of an Electric Rope Shovel for Different Operators
department or school: Applied Science, Faculty of
department or school: Non UBC
department or school: Mining Engineering, Keevil Institute of
data provider: DSpace
identifier citation: Minerals 6 (2): 48 (2016)
creator: Babaei Khorzoughi, Mohammad
creator: Hall, Robert
issued: 2019-05-24T17:50:34Z
issued: 2016-05-25
description: A performance monitoring study of an electric rope shovel operating in an open pit coal mine was conducted. As the mining industry moves toward higher productivity, profitability and predictability, the need for more reliable, productive and efficient mining shovels increases. Consequently, it is critical to study the productivity of these machines and to understand the effect of different operational parameters on that. In this paper a clustering analysis is performed to classify shovel digging effort and behaviour based on digging energy, dig time and payload per pass. Then the influence of the operator on the digging efficiency and productivity of the machine is analyzed with a focus on operator technique during digging. A statistical analysis is conducted on different cycle time components (dig time, swing time, return time) for different operators. In addition to time components, swing and return angles as well as loading rate and mucking rate are observed and analyzed. The results of this study help to understand the effect of different operators on the digging productivity of the shovel and then to set the best operator practice.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/70313
note: mineralsArticleA Study of Digging Productivity of an Electric RopeShovel for Different OperatorsMohammad Babaei Khorzoughi 1,* and Robert Hall 21 Norman B. Keevil Institute of Mining Engineering, University of British Columbia, Vancouver,BC V6T 1Z4, Canada2 School of Mining and Petroleum Engineering, University of Alberta, Edmonton, AB T6G 2W2, Canada;rhall1@ualberta.ca* Correspondance: mbabaei@alumni.ubc.ca; Tel.: +1-604-368-0667Academic Editor: Tuncel M. YegulalpReceived: 21 January 2016; Accepted: 13 May 2016; Published: 25 May 2016Abstract: A performance monitoring study of an electric rope shovel operating in an open pitcoal mine was conducted. As the mining industry moves toward higher productivity, profitabilityand predictability, the need for more reliable, productive and efficient mining shovels increases.Consequently, it is critical to study the productivity of these machines and to understand the effect ofdifferent operational parameters on that. In this paper a clustering analysis is performed to classifyshovel digging effort and behaviour based on digging energy, dig time and payload per pass. Thenthe influence of the operator on the digging efficiency and productivity of the machine is analyzedwith a focus on operator technique during digging. A statistical analysis is conducted on differentcycle time components (dig time, swing time, return time) for different operators. In addition to timecomponents, swing and return angles as well as loading rate and mucking rate are observed andanalyzed. The results of this study help to understand the effect of different operators on the diggingproductivity of the shovel and then to set the best operator practice.Keywords: electric rope shovels; productivity; digging energy; operator; digging time1. IntroductionLoading efficiency has a critical role in the success of the mining process as the loading equipmentis the source of ore supply [1] or waste removal. An efficient loading practice can help to increaseproduc…
has type: Article
is shown at: 10.14288/1.0378986
language: eng
peer review status: Reviewed
provider: Vancouver : University of British Columbia Library
publisher: Multidisciplinary Digital Publishing Institute
publisher DOI: 10.3390/min6020048
rights: CC BY 4.0
rights URI: https://creativecommons.org/licenses/by/4.0/
scholar level: Faculty
subject: Electric rope shovels
subject: Productivity
subject: Digging energy
subject: Operator
subject: Digging time
type: Text
identifier URI: http://hdl.handle.net/2429/70313