This article, while primarily about lithium extraction, has implications for AI because optimizing DLE processes such as those used by ILiAD Technologies will inevitably rely on advanced AI/ML algorithms for process control, predictive maintenance, and resource optimization. The deployment of ILiAD's DLE pilot unit at Rio Tinto's Sal de Vida site signals a move towards data-driven decision-making in resource extraction, where AI will play an increasingly vital role in maximizing efficiency and minimizing environmental impact across the energy, utilities and manufacturing sectors.
In the Energy & Utilities and Manufacturing & Industrial sectors, AI-driven optimization of lithium extraction can significantly reduce production costs, increase lithium supply, and decrease the environmental footprint of battery production. This will impact the competitiveness of battery manufacturers, electric vehicle producers, and energy storage solutions providers.
Operational impact: Operators can anticipate a shift towards more data-driven decision-making in lithium extraction. The deployment of ILiAD's DLE technology, possibly incorporating AI, might result in more efficient resource utilization, reduced environmental impact, and improved overall operational performance. Expect a need for skilled personnel capable of managing and interpreting data generated by these advanced systems, and a potential shift in maintenance schedules and procedures to accommodate automated operations.