Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Prudencio, Gerald, Pino, Diego, Arauzo, Luis, Raymundo, Carlos
Formato: artículo
Fecha de Publicación:2019
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/656294
Enlace del recurso:http://hdl.handle.net/10757/656294
Nivel de acceso:acceso embargado
Materia:LHD multiple linear regression
Productivity
Underground mining
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network_name_str UPC-Institucional
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dc.title.en_US.fl_str_mv Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
title Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
spellingShingle Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
Prudencio, Gerald
LHD multiple linear regression
Productivity
Underground mining
title_short Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
title_full Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
title_fullStr Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
title_full_unstemmed Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
title_sort Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
author Prudencio, Gerald
author_facet Prudencio, Gerald
Pino, Diego
Arauzo, Luis
Raymundo, Carlos
author_role author
author2 Pino, Diego
Arauzo, Luis
Raymundo, Carlos
author2_role author
author
author
dc.contributor.author.fl_str_mv Prudencio, Gerald
Pino, Diego
Arauzo, Luis
Raymundo, Carlos
dc.subject.en_US.fl_str_mv LHD multiple linear regression
Productivity
Underground mining
topic LHD multiple linear regression
Productivity
Underground mining
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2021-06-01T12:35:44Z
dc.date.available.none.fl_str_mv 2021-06-01T12:35:44Z
dc.date.issued.fl_str_mv 2019-01-01
dc.type.en_US.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/656294
dc.identifier.journal.en_US.fl_str_mv IMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings
dc.identifier.eid.none.fl_str_mv 2-s2.0-85066016160
dc.identifier.scopusid.none.fl_str_mv SCOPUS_ID:85066016160
dc.identifier.isni.none.fl_str_mv 0000 0001 2196 144X
url http://hdl.handle.net/10757/656294
identifier_str_mv IMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings
2-s2.0-85066016160
SCOPUS_ID:85066016160
0000 0001 2196 144X
dc.language.iso.en_US.fl_str_mv eng
language eng
dc.rights.en_US.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.en_US.fl_str_mv application/html
dc.publisher.en_US.fl_str_mv International Institute of Informatics and Systemics, IIIS
dc.source.es_PE.fl_str_mv Universidad Peruana de Ciencias Aplicadas (UPC)
Repositorio Académico - UPC
dc.source.none.fl_str_mv reponame:UPC-Institucional
instname:Universidad Peruana de Ciencias Aplicadas
instacron:UPC
instname_str Universidad Peruana de Ciencias Aplicadas
instacron_str UPC
institution UPC
reponame_str UPC-Institucional
collection UPC-Institucional
dc.source.journaltitle.none.fl_str_mv IMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings
dc.source.volume.none.fl_str_mv 2
dc.source.beginpage.none.fl_str_mv 81
dc.source.endpage.none.fl_str_mv 86
bitstream.url.fl_str_mv https://repositorioacademico.upc.edu.pe/bitstream/10757/656294/1/license.txt
bitstream.checksum.fl_str_mv 8a4605be74aa9ea9d79846c1fba20a33
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio académico upc
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spelling 5cdbb21056e7c626a4655dd6e33a79f55328bed295b046ec06c0a3dabf0684e63a628d19f907dee88fa42516e5f63ca7500f1b29165990ab4ce165cbf28f5e4ccd9500Prudencio, GeraldPino, DiegoArauzo, LuisRaymundo, Carlos2021-06-01T12:35:44Z2021-06-01T12:35:44Z2019-01-01http://hdl.handle.net/10757/656294IMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings2-s2.0-85066016160SCOPUS_ID:850660161600000 0001 2196 144XEl texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.The current study is based on a multiple linear regression analysis with an objective to formulate an equation related to the productivity analysis of LHD equipment using independent variables such as the effective utilization of the equipment. To identify the independent variables, main productive factors, such as the actual capacity of the buckets, the transport cycles in the cleaning process, and the performance by means of curves, were analyzed. Comparisons of a Peruvian underground mine case study exhibited that the battery-powered equipment denoted similar production efficiencies to that exhibited by its diesel counterparts; however, the three-tier approach observed that the battery-powered equipment could achieve production efficiencies that are up to 13.8% more as compared to that achieved using its diesel counterparts because of increased effective utilization that can be attributed to long MTBF. The results of this study exhibit that LHDs under battery-powered storage are feasible for underground mining not only because of the fact that they do not emit any polluting gases, which helps to mitigate pollution, but also because of their good production performance that can be considered to be an important pillar in deep mining. Copyright 2019.application/htmlengInternational Institute of Informatics and Systemics, IIISinfo:eu-repo/semantics/embargoedAccessUniversidad Peruana de Ciencias Aplicadas (UPC)Repositorio Académico - UPCIMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings28186reponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCLHD multiple linear regressionProductivityUnderground miningProductivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peruinfo:eu-repo/semantics/articleLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/656294/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51false10757/656294oai:repositorioacademico.upc.edu.pe:10757/6562942021-06-01 12:35:45.209Repositorio académico upcupc@openrepository.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Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
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