Indicadores Claves de Desempeño y Power BI para mejorar la productividad en perforación y voladura de la Unidad Minera Americana
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Date
2024-07
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Universidad Nacional de Trujillo
Abstract
El objetivo principal de la investigación fue mejorar la productividad en perforación y
voladura de la Unidad Minera Americana mediante el uso de Indicadores Claves de Desempeño
y Power BI.
La metodología que utilizó fue de diseño cuasiexperimental, descriptivo transversal, de
tipo cuantitativo. La muestra se conformó por los procesos de perforación y voladura llevada a
cabo en la unidad minera. La data fue recolectada mediante el análisis documental, así mismo
se empleó la probabilidad para el control de calidad de datos, siendo menor al 5% con un valor
crítico de 2.76 y un estadístico F de 1369.14. Los resultados indicaron que se logró evaluar los
indicadores clave de desempeño más relevantes para los procesos de perforación y voladura en
la Unidad Minera, las cuales fueron el avance de perforación, factor de avance, volumen de
roca fragmentada, factor de carga, factor de potencia y la sobrerotura. Asimismo, la
implementación de Power BI permitió analizar y visualizar los datos de KPIs, donde se obtuvo
un total de 5789.16 m de avance, factor promedio de 39.52 kg/m, 78280.69 m3 de roca
fragmentada, factor de carga promedio de 3.14 kg/m3, factor de potencia promedio de 1.16
kg/ton y una sobrerotura promedio de 13% en un periodo de setiembre 2023 a febrero de 2024.
Se incremento el avance de perforación de 10 y 14 ft en un 6.90% y volumen de roca
fragmentada en 12.96%, también se redujo el facto de avance, factor de carga, factor de
potencia y sobrerotura en un 9.21%, 5.50%, 5.78% y 41.18%, respectivamente.
Finalmente se llega a la conclusión que mediante el uso de Indicadores Claves de
Desempeño y Power BI se mejoró la productividad en perforación y voladura de la Unidad
Minera Americana.
The main objective of the research was to improve the drilling and blasting productivity of the Americana Mining Unit through the use of Key Performance Indicators and Power BI. The methodology used was a quasi-experimental, cross-sectional descriptive, quantitative design. The sample consisted of the drilling and blasting processes carried out in the mining unit. The data was collected through documentary analysis, and the probability was also used for data quality control, being less than 5% with a critical value of 2.76 and an F statistic of 1369.14. The results indicated that it was possible to evaluate the most relevant key performance indicators for the drilling and blasting processes in the Mining Unit, which were the drilling advance, advance factor, volume of fragmented rock, load factor, power factor and overburden. Likewise, the implementation of Power BI allowed to analyze and visualize the KPIs data, where a total of 5789.16 m of advance was obtained, average factor of 39.52 kg/m, 78280.69 m3 of fragmented rock, average load factor of 3.14 kg/m3, average power factor of 1.16 kg/ton and an average overburden of 13% in a period from September 2023 to February 2024. The drilling advance of 10 and 14 ft increased by 6.90% and the volume of fragmented rock increased by 12.96%, also the advance rate, load factor, power factor and overburden were reduced by 9.21%, 5.50%, 5.78% and 41.18%, respectively. Finally, it is concluded that the use of Key Performance Indicators and Power BI improved the drilling and blasting productivity of the American Mining Unit.
The main objective of the research was to improve the drilling and blasting productivity of the Americana Mining Unit through the use of Key Performance Indicators and Power BI. The methodology used was a quasi-experimental, cross-sectional descriptive, quantitative design. The sample consisted of the drilling and blasting processes carried out in the mining unit. The data was collected through documentary analysis, and the probability was also used for data quality control, being less than 5% with a critical value of 2.76 and an F statistic of 1369.14. The results indicated that it was possible to evaluate the most relevant key performance indicators for the drilling and blasting processes in the Mining Unit, which were the drilling advance, advance factor, volume of fragmented rock, load factor, power factor and overburden. Likewise, the implementation of Power BI allowed to analyze and visualize the KPIs data, where a total of 5789.16 m of advance was obtained, average factor of 39.52 kg/m, 78280.69 m3 of fragmented rock, average load factor of 3.14 kg/m3, average power factor of 1.16 kg/ton and an average overburden of 13% in a period from September 2023 to February 2024. The drilling advance of 10 and 14 ft increased by 6.90% and the volume of fragmented rock increased by 12.96%, also the advance rate, load factor, power factor and overburden were reduced by 9.21%, 5.50%, 5.78% and 41.18%, respectively. Finally, it is concluded that the use of Key Performance Indicators and Power BI improved the drilling and blasting productivity of the American Mining Unit.
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Keywords
TECHNOLOGY::Civil engineering and architecture::Geoengineering and mining engineering::Mining engineering