dc.creatorPrudencio, Gerald
dc.creatorPino, Diego
dc.creatorArauzo, Luis
dc.creatorRaymundo, Carlos
dc.date.accessioned2021-06-01T12:35:44Z
dc.date.accessioned2024-05-07T02:09:46Z
dc.date.available2021-06-01T12:35:44Z
dc.date.available2024-05-07T02:09:46Z
dc.date.created2021-06-01T12:35:44Z
dc.date.issued2019-01-01
dc.identifierhttp://hdl.handle.net/10757/656294
dc.identifierIMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings
dc.identifier2-s2.0-85066016160
dc.identifierSCOPUS_ID:85066016160
dc.identifier0000 0001 2196 144X
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9325340
dc.description.abstractThe 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.
dc.languageeng
dc.publisherInternational Institute of Informatics and Systemics, IIIS
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.sourceUniversidad Peruana de Ciencias Aplicadas (UPC)
dc.sourceRepositorio Académico - UPC
dc.sourceIMCIC 2019 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings
dc.source2
dc.source81
dc.source86
dc.subjectLHD multiple linear regression
dc.subjectProductivity
dc.subjectUnderground mining
dc.titleProductivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru
dc.typeinfo:eu-repo/semantics/article


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