THE LEADER VOLUME 11 • NUMBER 5
Leadership in mine automation
Founder and Publisher John Chadwick B. Sc. Min Eng Email: john @ im-mining. com
Editor Paul Moore B. Sc( Hons), M. Sc. Email: paul @ im-mining. com
Editorial Board Professor Malcolm Scoble Robert E. Hallbauer Chair in Mining Engineering., University of BC, Vancouver
Peter Knights BMA Chair & Prof. of Mining Engineering University of Queensland
Stephen Stone West One Management Perth, Western Australia
Dr. Andrew M. Robertson President, Robertson GeoConsultants Vancouver, Canada.
Ed McCord Project Consultant Caterpillar Global Mining, USA
Jason Nitz Fleet Management & Dispatch Superintendent Newmont Mining Corporation, USA
Dr Terry Mudder Managing Director, TIMES Ltd, USA
Simon Tarbutt Consultant, Santiago, Chile
Dr. Mike Daniel Comminution Process Consultant CMD Consulting Pty Ltd
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ISSN 1747-146X
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Warrick Ranson, Rio Tinto’ s Head of Productivity Development, Technology & Innovation, presented Driving Productivity through Strategic Partnerships to Austmine late last year.
He explained that in June“ we announced the completion of our staged expansion program in the Pilbara to 360 Mt / y [ iron ore ]. This has been one of Australia’ s largest mining projects and involved a total capital spend of $ 14.7 billion, with the project centred on the expansion of port and shipping capacity, additional rail and power infrastructure, and brownfield mine expansions. On-time delivery and at a capital cost significantly below initial estimates were indicators of success. Technology & Innovation played a critical role in this, as did collaboration.”
He cautioned that:“ In a business of complexity, problems are not singular in nature: a blockage or challenge in one area of our value chain has repercussions throughout. Multidisciplinary solutions are critical. There are seldom textbook solutions, and‘ what worked’ at one site, or in one country, won’ t always work seamlessly in another.” He stressed the need for engineering through“ trial and error, through novel practice rather than best practice, and through the collaboration of many.”
Rio Tinto’ s Mine of the Future™ had its visionary beginnings back in 2008 and identified“ enormous potential for automation” taking“ learnings from industries such as aeronautics and food production, this project has revolutionised the identification, extraction and transportation of minerals.” Partners include Atlas Copco, Caterpillar, Schneider Electric and Metso CISA.
In Western Australia, the Iron Ore group operates 15 mines, 1,700 km of rail, four ports and three power stations across the Pilbara, an area more than double the size of the Australian state of Victoria. There is an Operations Centre, situated some 1,500 km away in Perth and‘ whole-of-mine’ seamless automation drives productivity.
Rio is the world’ s largest owner and operator of autonomous trucks: a fleet of 69 units operating across three sites. Meanwhile, the AutoHaul ® train network will be the world’ s first fully autonomous heavy haul, longdistance railway system, but it is behind schedule.
“ AutoHaul will claw back almost two hours of run time, per train, per day. It will also eliminate the need for 70,000 km of remote area driving that is required each week to get drivers to shift change locations, and will provide increased flexibility in scheduling.”
The Automated Drilling System( ADS) allows blastholes to be drilled without the need for an on-drill operator.“ Our West Angelas mine is the world’ s first full-time autonomous drill mine, with seven rigs in operation that have now drilled over two million metres,” with a 10 % increase in equipment utilisation in under a year.“ We are working at introducing ADS at Yandicoogina and other mine sites across the Pilbara. Importantly, technologies such as autonomous drills significantly reduce employee exposure to the hazards and risks associated with operating this type of heavy duty equipment.”
Rio Tinto is reducing capital expenditure and operating costs through reduced labour costs, improving equipment utilisation, increasing orebody recovery, improving equipment productivity, and reducing processing variability and raw material consumption. There are major improvements in health and safety performance. As one example, the Pilbara autonomous truck fleet has improved utilisation- outperforming the manned fleet by an average of 12 %- and revealed a 13 % reduction in load and haul costs due to greater efficiency.
A year prior to this presentation, Rio Tinto launched its RTVis™ development at IMARC. Now, Ranson reported,“ it forms the visual display component of a much more significant system that we’ ve been developing – our Mine Automation System( MAS). If you can envisage an ultrasound embedded beneath the earth in an orebody, enabling a 3D image of the deposit in real time, you’ ll have some idea of the initial applications we talked about.
“ The 3D image produced matches the geological model inside the pit to GPS-generated block models to mine and extract ore down to metres, and even centimetres. Since the launch we have significantly expanded the system’ s capability- we don’ t just visualise the deposit but now visualise the whole mine, enabling us to optimise the use of equipment as well as the orebody.”
The known geological model, mine operational constraints, operating costs and revenues are downloaded to autonomous drills“ that not only execute the pattern but also collect penetration rate data that we transfer back into MAS. Sampling of the blast cones is then carried out and also fed into MAS, generating charging information for downloading to our prototyped smart-charge truck that fills the drill holes with explosives with predictive precision. Again, actual quantities charged to each hole are recorded and fed back into MAS. The blast occurs; digging commences; and we begin to haul through our autonomous or manned fleet. The location of our haul trucks is then tracked such that we know exactly where the material comes from as it makes its way through the plant.
“ Analysis of that data enables the inference of particle size distribution results which we then compare with the intended outcomes. The difference between the predicted and measured results is used to update the geological parameters in the blast optimisation model … and the cycle continues.”
That’ s a very impressive advance in just eight years. John Chadwick
Founder john @ im-mining. com
MAY 2016 | International Mining 3