From Point Solutions to Predictive Power: How Machine Learning Can Revolutionize Tailings Management

Author(s) R.Hunter, Z.Forootan, D.Molina
Tailings 2024

The need for data-driven digital solutions for tailings management has been growing for several years. While many of the systems have been beneficial as point solutions, the disparate nature of these systems and their produced data has made it difficult, if not impossible, for operators to gain comprehensive insights into the complex interdependencies shaping tailings’ behaviour. As a result, the push toward integrated operations digitization seems inevitable. Interconnected factors such as technological advancements, heightened environmental and social awareness, evolving regulatory and compliance guidelines, changing investor and public expectations, and the need for economic efficiency are creating an environment where a Machine Learning (ML)-first approach to managing risk and plan alignment is not only an exciting opportunity for the mining industry, but is critical for future success. This paper will present how this transition to holistic operations digitization and the adoption of holistic software designed to collect and streamline all data with a ML-first approach will allow mining companies to more effectively benefit from newer generative Artificial Intelligence (AI) and ML models, evolve tailings management processes, and improve decision-making.