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Unplanned Dilution Prediction In Open Stope Mining: Developing New Design Charts Using Artificial Neural Network Classifier, Sultan Korigov, Amoussou Coffi Adoko, Fhatuwani Sengani

Journal of Sustainable Mining

Minimizing dilution is essential in open stope mine design as excessive unplanned dilution can compromise the operation's profitability. One of the main challenges associated with the empirical dilution graph method used to design open stopes is how to determine the boundary of the dilution zones objectively. Hence, this paper explores the implementation of machine learning classifiers to bridge this gap in the conventional dilution graph method. Stope performance data consisting of the stope dilution (unplanned dilution), the modified stability number, and the hydraulic radius were compiled from a mine located in Kazakhstan. First, the conventional dilution graph methods were used …