en.Wedoany.com Reported - An artificial intelligence-driven system introduced by MMG at its Dugald River zinc mine in Queensland, Australia, has demonstrated value within less than three months of operation, according to an analysis conducted one year after its deployment.

Developed by professional services firm Hatch, the system utilizes a digital twin model of the Dugald River flotation circuit, aiming to enhance zinc recovery rates and plant profitability. The technology combines process modeling, machine learning, and advanced process control to automatically adjust plant operations based on changes in feed material.

Tim Akroyd, General Manager of the Dugald River mine, stated that digital twin technology represents the next step forward for the mine, building on significant performance improvements achieved through traditional methods. Akroyd noted that the operations team focuses on identifying and implementing the right technologies to continuously drive safety and performance improvements. The system acts like an always-on assistant, constantly adjusting plant operations to extract the maximum amount of zinc from each ton of ore processed.

After one year of operation, MMG reports that the system has surpassed previous performance benchmarks while bringing greater consistency to the processing plant. Alec Malcolm, Senior Metallurgist at Dugald River responsible for on-site project implementation, pointed out that the results are positive and exceed previous performance benchmarks. He expressed encouragement regarding the system's flexibility and its ability to be tailored to different process objectives.

Warwick Smith, Global Business Lead for Digital Twins at Hatch, stated that close collaboration with the metallurgical and operational teams at Dugald River helped reduce implementation risks and build confidence in the technology. Smith noted that by adopting a progressive, metallurgy-focused approach to applying digital twin technology in complex processes—from preliminary feasibility studies to phased implementation—the on-site team was able to advise on the development process and closely mitigate overall implementation risks. As trust was gradually established, Dugald River has achieved a level of autonomous, AI-driven plant control that is rare in mineral processing.