Ingeniero Civil de Minas / La tronadura es un proceso clave dentro de cualquier faena minera, por lo cual se hace necesario su entendimiento global para minimizar los costos de las operaciones posteriores: carguío, transporte, chancado y molienda. Actualmente la faena minera El Soldado de Anglo American está probando alternativas de diseño en perforación y tronadura, lo que dio origen a este estudio, cuya finalidad es cuantificar los resultados del proceso, para luego obtener las variables que entreguen el mayor beneficio global mina-planta. En el presente informe se cuantificó el resultado de un conjunto de tronaduras mediante la medición granulométrica y su incidencia en los procesos aguas abajo. Específicamente se cuantificó la variación del rendimiento efectivo de las palas y la variación de las toneladas por hora del molino SAG. Usando el software Split se logró medir la granulometría en todos los rangos de tamaños. El rendimiento de las palas y las toneladas por hora del SAG se obtuvieron de la base de datos y del dispatch de la mina. Mediante el estudio de los resultados de la tronadura en conjunto con un análisis estadístico, se obtuvieron las variables relevantes del proceso, que son: la litología, la zona, el taco, pero la más importante es el factor de carga. Se obtuvieron modelos granulométricos y de rendimiento de las palas, en base a las variables relevantes, principalmente en torno al factor de carga. Mediante dichos modelos y teniendo la información de los requerimientos óptimos de carguío y de la alimentación al molino SAG, se calcularon las variables de diseño de perforación y tronadura que maximizan el beneficio neto mina-planta. Finalmente, se realizó un análisis económico, comparando el actual escenario de operación con el escenario propuesto. La recomendación principal es usar un explosivo más denso y distintas configuraciones de mallas, dependiendo de la fase y del sector a perforar. Otra recomendación complementaria es el cumplimiento del diseño propuesto en terreno; vale decir, asegurar el factor de carga por pozo y por disparo.

The characterization of rock properties is a vital task in the challenge for hard rock mining operation. A simplified and straightforward characterization of rock properties provides information about the safety of ground structure (e.g. slope, tunnel, etc.), and the strategy to improve productivity in terms of rock breakage process. The penetration-rate of drilling has been proposed to quantify the comminution characteristics of rock by virtue of real-time logging of drilling performance otherwise the data is obtained from a time- and cost-consuming laboratory test; this is called measurement while drilling. In the mining industry, this technique can be a useful tool that has allowed for the meticulous and routine data collection of geological information from blasthole drilling operations. In this study, the mechanical performance of drill and its interaction with the rock properties is investigated in laboratory scale. The rock properties include tensile strength, hardness, and grindability, which is considered as the influential parameters of the required energy consumption for the comminution processes. For sandstone samples, the penetration-rate data shows a good correlation with tensile strength, hardness, and Bond work index; this implies that penetration-rate data can be a good indicator to estimate comminution characteristics. Additionally we carried out the same test with limestone samples. Second, field study is conducted to investigate the interaction between current blast design and rock fragmentation. Fabricating the blast design and fragmentation through the blast operation might enable to construct proper strategy to reduce the energy cost of downstream processes including crushing and grinding by using the rock characteristics measured from the blasthole drilling. The concept of this process is a part of Mine-to-Mill optimization. The thesis proposed the blueprint of Mine-to-Mill optimization, providing a guideline for further in-situ research.

Mine to Mill optimization is considered as a key concept for metal mining recently. Targeting operational best practices on a highly varying environment is challenging. Impact of underperformed basic operations such as drilling and blasting will sustain this inefficiency in mineral processing. Data provided for each of these operations from software and hardware utilized on field reached a level where advanced data analytics becomes applicable. In order to represent the operations as close to reality, an integrated layer of data where transactional and process based data lives is crucial. Data warehousing and data mining are alternative tools that rely on a robust data structure. Data mining utilizes the integrated data layer for pattern discovery within the data itself. Relations that are unknown for now can be investigated by data mining algorithms that rely on vast amount of data. Empirical equations that are based on a limited set of data could be improved by using data mining algorithms. The main objective of optimizing the mine to mill value chain also challenges the concept of providing real-time feedback. This research proposes a data-driven mine-to-mill framework for modern mines.