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

      Prudencio, Gerald; Pino, Diego; Arauzo, Luis; Raymundo, Carlos (International Institute of Informatics and Systemics, IIIS, 2019-01-01)
      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.
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    • Reuse method for deposits of polymetallic tailings in a state of abandonment through the application of mineral flotation

      Anchiraico, Anthony; Bazo, José; Aramburú, Vidal; Raymundo, Carlos (Springer Science and Business Media Deutschland GmbH, 2019-01-01)
      In the mining industry, due to the extraction and processing of ore, a significant amount of tailings are produced which are discharged into deposits. In some cases, these are in contact with effluents and generate acid waters that pollute the environment and affect the health of the inhabitants. Additionally, these tailings within their composition contain valuable metals that can be reused through a process of mineral flotation. As a part of this research, a study based exclusively on laboratory tests was performed on the tailings deposit located in the Recuay–Peru district, where the presence of concentrations of Pb, Zn, and Ag at 48.36% was obtained, 23% and 250 g/TM. Thus, this study aims to take advantage of polymetallic tailings deposits that are in an abandonment state by extracting valuable ore through the flotation process based on their chemical composition and mineralogical characterization.
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    • SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations

      Ziegler-Barranco, Ana; Mera-Barco, Luis; Aramburu-Rojas, Vidal; Raymundo, Carlos; Mamani-Macedo, Nestor; Dominguez, Francisco (Springer, 2020-01-01)
      Several factors affect the activities of the mining industry. For example, accident rates are critical because they affect company ratings in the stock market (Standard & Poors). Considering that the corporate image is directly related to its stakeholders, this study conducts an accident analysis using quantitative and qualitative methods. In this way, the contingency rate is controlled, mitigated, and prevented while serving the needs) of the stakeholders. The Bayesian network method contributes to decision-making through a set of variables and the dependency relationships between them, establishing an earlier probability of unknown variables. Bayesian models have different applications, such as diagnosis, classification, and decision, and establish relationships among variables and cause–effect links. This study uses Bayesian inference to identify the various patterns that influence operator accident rates at a contractor mining company, and therefore, study and assess the possible differences in its future operations.
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    • Six sigma model optimized for reducing downtime in an open-pit mine

      Gargate, Josemaria; Fung, Sian A.; Jara, Juan; Raymundo, Carlos (Springer Science and Business Media Deutschland GmbH, 2019-01-01)
      Currently, in open-pit mining operations, the highest cost among all processes is that of transporting trucks, whether in fuel, roads, tires, or spare parts, among other factors. Therefore, this article proposes the use of the Six Sigma methodology of continuous improvement as a quality management tool to reduce the downtime of the truck fleet to obtain better productivity in operations. The results of the investigation in the case study allowed to visualize that with the election of an optimal fleet appropriate for the conditions given in a mining project, the values of productivity and efficiency improve considerably. This is reflected in a better use of the machinery and in the reduction of unproductive times.
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    • Six sigma-based optimization model in hauling cut and fill exploitation activities to reduce downtime in underground mines in Peru

      Rojas, Kevin; Aramburú, Vidal; Ramos, Edgar; Raymundo, Carlos; Moguerza, Javier M. (Springer Verlag, 2019-06-06)
      In the mining industry, the mining cycle is a very important part in the operating stage of every mining unit. Through the exploitation method used, the mining cycle provides mineral ore, which subsequently undergoes various metallurgical processes and its commercialization and thereby generates profits to the mining company. Currently, within this cycle, the hauling and transportation stages are those that have a lower efficiency with respect to the drilling and blasting stages. Therefore, the sector is always seeking effective ways to optimize these processes, reduce downtime and increase productivity. Six Sigma is a technique that allows for the continuous process improvement. In this study, the factors that generate inefficiency in the hauling cycle are determined, and alternatives are implemented to solve the main problem and improve the operations cycle.
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