Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision.
Mining is one of the major components of the Australian ....Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision.
Mining is one of the major components of the Australian economy. This project will improve mining automation and contribute to a more efficient industry, capable to compete internationally in the new globalisation context. Efficient extraction will also reduce the human impact and will be a significant factor for an environmentally sustainable development. Read moreRead less
Genetic Algorithms for Open-Cut Mine Scheduling. Open-cut mining depends heavily on long-term scheduling. This project will apply a novel artificial intelligence method, genetic algorithms, to mine scheduling. The aim is to create an improved scheduler as a drop-in replacement for today's methods, which generally assume perfect knowledge of the ore body and future prices and costs. This project will optimize schedules that cope with uncertainties, by searching the possible scenarios to automa ....Genetic Algorithms for Open-Cut Mine Scheduling. Open-cut mining depends heavily on long-term scheduling. This project will apply a novel artificial intelligence method, genetic algorithms, to mine scheduling. The aim is to create an improved scheduler as a drop-in replacement for today's methods, which generally assume perfect knowledge of the ore body and future prices and costs. This project will optimize schedules that cope with uncertainties, by searching the possible scenarios to automatically find the best options for different future contingencies. This will produce flexible schedules, to maintain mine viability and job security despite unpredictable economic fluctuations. About 40% of Australia's exports come from mining, so this proposal will benefit the nation's economy, and make secure mining jobs in rural and regional areas.Read moreRead less
Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combination ....Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combinations of different types of units. The complexity of typical flowsheet layouts will require new algorithms to discover improved designs in practical time, so parallel hardware, and new parallel EAs, will be utilised.
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Mathematics and computing for integrated stockyard-centric management of mining supply chains. Blended mineral products, such as coal and iron ore, make a strong contribution to Australia's economy. Blending occurs in stockpiles, so to realise product value, stockyard and supply chain operational plans must align with blend targets. This project will provide new mathematical and computational planning tools to maximise this value.
Making the Pilbara blend: agile mine scheduling through contingent planning. Mine scheduling is a challenging problem for Rio Tinto which annually mines more than 200 Million tonnes of iron ore. This project will develop agile scheduling techniques of great economic importance to Australia. Carefully planned scheduling reduces infrastructure and minimises environmental impacts, maximising regeneration after mining.