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Minerals 16 00060 by Mauricio is a document available to read on EtoBox.
This study presents a stochastic model using Bayesian networks to analyze SAG mill production and power in the Chilean copper mining industry, addressing the uncertainties and nonlinear dependencies inherent in the process. The model, validated with operational data, emphasizes causal inference and probabilistic scenario evaluation rather than exact regression, identifying key drivers such as water feed and solids percentage. The findings suggest that this approach can enhance process control and support de
- Author
- Mauricio
- Language
- EN