Aumento de la calidad catódica en Minera Centinela: análisis estadístico para optimizar la producción de cátodos de cobre grado A.
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad de Concepción
Abstract
A partir de la necesidad de una demanda de mayor producción, la planta hidrometalúrgica de Minera Centinela, que cuenta con una capacidad de diseño de 105.273 toneladas producidas al año, enfrenta un desafío operacional para conseguir 95.903 toneladas de cátodos de cobre en 2024 (i.e., 36,55 % superior al año 2023) y condiciones de materialidad exigentes para cumplir con calidades catódicas adecuadas en la meta de producción. En este contexto, se estudia el comportamiento de la calidad catódica respecto de algunas variables predeterminadas que permiten proyectar una configuración óptima en estas condiciones operacionales.
En el desarrollo de esta memoria, se identifican las principales variables para definir y analizar el comportamiento de calidad catódica grado A, a través de la manipulación de la data histórica de variables predictivas (i.e., concentración de reactivos Verguar y DXG-F7, concentración de ácido y cobre en el electrolito pobre, temperatura de electrolito, densidad de corriente y masa de cada placa de cobre electroobtenida) que dan respuesta a la calidad de cátodos grado A (%).
En primer lugar, se realiza un análisis estadístico descriptivo de la calidad catódica de naturaleza discreta y definida como una categoría de clasificación de calidad ideal (i.e., intervalos de 80%, 90%, 100% calidad grado A). Como resultado de este primer análisis, se obtiene una configuración óptima que asegura al menos un 95% de calidad grado A en los parámetros de producción habituales. La finalidad de este estudio categórico, es proporcionar los fundamentos necesarios para orientar el objetivo de maximización en un intervalo de calidad grado A que necesita ser aumentado.
El incremento se lleva a cabo con un análisis de estadístico para variables que responden a una calidad catódica de comportamiento continuo, debido a que las interacciones entre variables predictoras que afectan la calidad son diferentes a la de una categoría ideal. De este análisis, se obtiene un modelo de regresión multivariable para un comportamiento de parámetros con una respuesta de calidad inferior al 70%, concluyendo que el modelo predictivo logra un máximo 83% de la calidad grado A e identifica los valores de las variables más influyentes de este intervalo (i.e., densidad de corriente, concentración de ácido y cobre en el electrolito pobre, y la aplicación de reactivo Verguar).
Para incrementar la calidad catódica, es crucial acompañar la maximización con un seguimiento constante en el desempeño de los componentes de la nave de electroobtención y realizar un monitoreo continuo de los métodos y prácticas operacionales identificadas como deficientes. Este enfoque integral asegura un mayor porcentaje de cátodos grado A para las exigencias operacionales del 2024.
Given the increasing demand for higher production, the hydrometallurgical plant of Minera Centinela, designed for an annual output capacity of 105,273 tons, faces an operational challenge in achieving 95,903 tons of copper cathodes in 2024 (i.e., 35.06% higher than in 2023) under stringent material conditions to meet the required cathodic quality for the production target. In this context, the behavior of cathodic quality is analyzed with a statistical approach in relation to certain predetermined variables that allow for projecting an optimal configuration under these operational conditions. In the development of this report, the main variables for defining and analyzing the behavior of grade A cathodic quality have been identified through the manipulation of historical data from predictive variables (i.e., concentrations of Verguar and DXG-F7 reagents, acid and copper concentrations in the poor electrolyte, electrolyte temperature, current density, and mass of each electrowinning copper plate) that respond to the quality of grade A cathodes (%). First, a descriptive statistical analysis of the discrete nature of cathodic quality is conducted, defined as a classification category of ideal quality (i.e., intervals of 80%, 90%, 100% grade A quality). As a result of this initial analysis, an optimal configuration is obtained that ensures at least 95% grade A quality under standard production parameters. The aim of this categorical study is to provide the necessary foundations to guide the objective of maximizing the interval of grade A quality that needs to be increased. The increase is conducted through a statistical analysis of variables corresponding to the continuous behavior of cathodic quality, as the interactions between predictive variables affecting quality differ from those of an ideal category. From this analysis, a multivariable regression model is developed for parameters yielding a quality response below 70%, concluding that the predictive model achieves 83% grade A quality while identifying the most influential variable values within this range (i.e., current density, acid and copper concentrations in the poor electrolyte, and the application of the Verguar reagent). To enhance cathodic quality, it is crucial to accompany the maximization with constant monitoring of the performance of the electrowinning components and to conduct ongoing surveillance of the operational methods and practices identified as deficient. This comprehensive approach ensures a higher percentage of grade A cathodes to meet the operational demands of 2024.
Given the increasing demand for higher production, the hydrometallurgical plant of Minera Centinela, designed for an annual output capacity of 105,273 tons, faces an operational challenge in achieving 95,903 tons of copper cathodes in 2024 (i.e., 35.06% higher than in 2023) under stringent material conditions to meet the required cathodic quality for the production target. In this context, the behavior of cathodic quality is analyzed with a statistical approach in relation to certain predetermined variables that allow for projecting an optimal configuration under these operational conditions. In the development of this report, the main variables for defining and analyzing the behavior of grade A cathodic quality have been identified through the manipulation of historical data from predictive variables (i.e., concentrations of Verguar and DXG-F7 reagents, acid and copper concentrations in the poor electrolyte, electrolyte temperature, current density, and mass of each electrowinning copper plate) that respond to the quality of grade A cathodes (%). First, a descriptive statistical analysis of the discrete nature of cathodic quality is conducted, defined as a classification category of ideal quality (i.e., intervals of 80%, 90%, 100% grade A quality). As a result of this initial analysis, an optimal configuration is obtained that ensures at least 95% grade A quality under standard production parameters. The aim of this categorical study is to provide the necessary foundations to guide the objective of maximizing the interval of grade A quality that needs to be increased. The increase is conducted through a statistical analysis of variables corresponding to the continuous behavior of cathodic quality, as the interactions between predictive variables affecting quality differ from those of an ideal category. From this analysis, a multivariable regression model is developed for parameters yielding a quality response below 70%, concluding that the predictive model achieves 83% grade A quality while identifying the most influential variable values within this range (i.e., current density, acid and copper concentrations in the poor electrolyte, and the application of the Verguar reagent). To enhance cathodic quality, it is crucial to accompany the maximization with constant monitoring of the performance of the electrowinning components and to conduct ongoing surveillance of the operational methods and practices identified as deficient. This comprehensive approach ensures a higher percentage of grade A cathodes to meet the operational demands of 2024.
Description
Tesis presentada para optar al título de Ingeniera Civil Metalúrgica
Keywords
Minería, Hidrometalurgia