Case Study: a multinational metals and mining corporation improves chip size classification and cutter optimization with Valiance

Multinational Metals and Mining Corporation boosts chip-size conversion by 15% with Valiance

The customer, a multinational metals and mining corporation, faced a challenge in its diamond mining operations. The size of extracted rock chips varied based on the cutting machine parameters set by operators, and the client's heuristic approach could not quantify individual parameter contributions or their interactions. They engaged Valiance to build a solution that could determine the optimal cutter settings to produce the largest chip size.

Valiance developed a machine learning engine to build a mathematical relationship between the tunable parameters and output quality. Their solution involved a classification model that optimized parameters for specific depths and lithology. The tree-based model showed 78% accuracy, and Valiance's optimization converted approximately 60% of previously bad samples into good ones, improving the overall conversion rate by about 15%.

Multinational Metals and Mining Corporation