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

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.