Machine Learning Method For Ore/waste Classification In Mining

This article discusses the development of a methodology for identifying lithologies in underground mining using chemical analysis and measurement-while-drilling data. The research aims to validate an automated drilling system and utilize machine learning techniques to create a prediction model for defining ore/waste boundaries. The challenges of sampling and analyzing drilling chips in underground mining are also addressed.