The Modern Mine
Safety is our number one priority and we are committed to achieving zero harm, so that all of our colleagues return home safely, every day. We are developing a new generation of engineered controls to reduce exposure to risk in work processes. We are using existing modernisation technologies, introducing remotely operated machinery, such as automated drilling and blasting, and continuous hard rock cutting, to remove people from harm’s way.
A full-scale continuous hard rock cutting system was installed underground at our Mototolo PGMs mine. It is remotely operated, and consists of continuous cutting and material transport with integrated ground support.The system provides a number of benefits, including: improved productivity; a safer working environment, with fewer people working in the production stopes area, and reducing ore dilution. During 2024, the system will contribute to production at Mototolo and demonstrate a pathway to transition from conventional to fully mechanised operations in steeply dipping, narrow, tabular orebodies
Anglo American's first fleet of 30 autonomous mining trucks is fully operational at our Quellaveco copper mine in Peru, where they are working alongside six autonomous production drills controlled from the Integrated Operations Centre (IOC) some 20 km by road from the mine. During 2023, control of the autonomous truck system transitioned to the operations centre.
During 2023 we made considerable progress on the digitalisation of our business – bringing digital technologies to our mines to make them safer, to connect our people and support their productivity. Our digital strategy is based around connecting what we can – our vehicles, machinery, equipment and plants – to our control systems to help us automate processes and continuously monitor and improve them.
Over the past few years, we have introduced digital twins that allow us to comprehensively model many of our plants. These twins allow us to produce virtual copies of our major infrastructure for the purpose of scenario analysis, operator training and detailed virtual 3D reconstructions of plant infrastructure to improve operational maintenance planning. Our twins are linked to our plant control systems and maintenance planning systems to support hazard reduction and minimise plant downtime. These models are also used to tweak and adjust variables – at a fraction of the cost of making changes on our installed infrastructure.
We leverage machine learning to harness our data, including from a range of geoscience sources, such as soil samples, drill results and chemical assays. Machine learning allows us to model complex processes and are using this capability across the business. For example, we are applying machine learning to deliver a step-change in our drill core interpretation practices using Assisted Core Logging (ACL). ACL uses advanced sensing, machine robotics, the interconnectedness of in-field equipment and the scalability of cloud-based computing to improve the efficiency of our drilling workflow, augmenting expert knowledge with machine learning. Geologists are now able to search for similar textural patterns across multiple cores and log numerous zones simultaneously. This has reduced the time it takes create a lithology log by approximately 90%.
