Desarrollo de un simulador de eventos discretos para el análisis del sistema de carguío y transporte en minería a cielo abierto.
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Date
2026
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad de Concepción
Abstract
En este trabajo se desarrolla e implementa un simulador de eventos discretos orientado al análisis del sistema de carguío y transporte en minería a cielo abierto, como primera versión funcional del modelo. El problema abordado corresponde a la dificultad de analizar el
comportamiento dinámico de este sistema, en el cual la interacción entre camiones y puntos de servicio, la formación de colas y las restricciones de capacidad influyen directamente en la producción.
La herramienta se basa en una arquitectura backend–frontend, el backend implementa la lógica de simulación mediante Python y SimPy, mientras que el frontend proporciona una interfaz gráfica tridimensional interactiva. Esta separación desacopla el cálculo de la visualización, facilitando la construcción de escenarios y la interpretación de resultados.
El simulador permite realizar análisis del tipo "qué pasaría si", evaluando cómo variaciones en parámetros operacionales como velocidades de transporte, tiempos de carga y descarga, configuración de rutas y tamaño de flota afectan el tiempo de ciclo y la producción total.
Como salida, entrega indicadores claves de desempeño: producción total, toneladas por hora, tiempos de ciclo y tiempos de espera, permitiendo identificar cuellos de botella operacionales. Adicionalmente, incorpora simulación Monte Carlo mediante distribuciones probabilísticas y múltiples réplicas independientes, lo que permite analizar tanto el comportamiento promedio del sistema como su dispersión frente a la incertidumbre operacional.
Finalmente, se verificó que los resultados presentan tendencias coherentes al compararlos con casos en Excel y el software ProModel, respaldando la consistencia del modelo. El trabajo sienta las bases para una herramienta con alto potencial de desarrollo futuro, orientada
al apoyo a la toma de decisiones en sistemas de carguío y transporte minero
This work develops and implements a discrete-event simulator aimed at analyzing the loading and hauling system in open-pit mining, as a first functional version of the model. The problem addressed is the difficulty of analyzing the dynamic behavior of this system, in which the interaction between trucks and service points, queue formation, and capacity constraints directly affect production. The tool is based on a backend–frontend architecture: the backend implements the simulation logic using Python and SimPy, while the frontend provides an interactive three-dimensional graphical interface. This separation decouples computation from visualization, facilitating scenario building and result interpretation. The simulator enables "what-if" analyses, evaluating how variations in operational parameters such as hauling speeds, loading and dumping times, route configuration, and fleet size affect cycle time and overall production. As output, it provides key performance indicators: total production, tons per hour, cycle times, and waiting times, allowing the identification of operational bottlenecks. Additionally, it incorporates Monte Carlo simulation through probabilistic distributions and multiple independent replications, enabling analysis of both the average system behavior and its variability under operational uncertainty. Finally, the results were verified to exhibit consistent trends when compared against spreadsheet-based cases and the ProModel simulation software, supporting the model's consistency. This work lays the foundation for a tool with significant potential for future development, aimed at supporting decision-making in mining loading and hauling systems..
This work develops and implements a discrete-event simulator aimed at analyzing the loading and hauling system in open-pit mining, as a first functional version of the model. The problem addressed is the difficulty of analyzing the dynamic behavior of this system, in which the interaction between trucks and service points, queue formation, and capacity constraints directly affect production. The tool is based on a backend–frontend architecture: the backend implements the simulation logic using Python and SimPy, while the frontend provides an interactive three-dimensional graphical interface. This separation decouples computation from visualization, facilitating scenario building and result interpretation. The simulator enables "what-if" analyses, evaluating how variations in operational parameters such as hauling speeds, loading and dumping times, route configuration, and fleet size affect cycle time and overall production. As output, it provides key performance indicators: total production, tons per hour, cycle times, and waiting times, allowing the identification of operational bottlenecks. Additionally, it incorporates Monte Carlo simulation through probabilistic distributions and multiple independent replications, enabling analysis of both the average system behavior and its variability under operational uncertainty. Finally, the results were verified to exhibit consistent trends when compared against spreadsheet-based cases and the ProModel simulation software, supporting the model's consistency. This work lays the foundation for a tool with significant potential for future development, aimed at supporting decision-making in mining loading and hauling systems..
Description
Tesis presentada para optar al título de Ingeniero/a Civil de Minas.
Keywords
Acarreo minero, Extracción metalúrgica, Minas