14 April 2015
Laser and radar scanners, as well as Global Navigation Satellite System (GNSS) technology have allowed driverless trucks and trains to become a reality in some key mining regions such as Western Australia, helping companies to continue in their drive for safer and more productive operations.
Russ Morrison believes that there are very few technical hurdles that now need to be overcome – the main challenge is the implementation of these sophisticated technologies. Highlighting some of the latest technology developments, Russ discusses the complexities surrounding automation and remote operation which, if not appropriately addressed, could hamper a company’s ability to reap the long term benefits including improved operational efficiency and a safer, more attractive working environment.
Automation is seen to be one of the most influential tools in helping the mining industry progress and develop with companies such as Rio Tinto leading the way. Mega-bots such as the 600 tonne (when fully loaded) driverless trucks which are now being used successfully in the Australian outback are now becoming part of the norm thanks to major developments in GNSS, Inertial Navigation System (INS), radar and laser technologies. The arrival of this enabling technology over the last ten years has resulted in a significant step change in the way the industry operates and the pace technological improvement shows no sign of abating.
The ever increasing demand for raw materials has created huge opportunities in the market. In remote areas, mining companies wishing to satisfy the demand and benefit on a commercial level have been unable to secure the level of skilled resource needed to accommodate such growth. Faced with a potential long-term skills shortage, mining companies have turned to technology, not to replace skilled labour but to augment it. That said the fundamental driver for automation and remote operation is largely down to the industry’s ongoing commitment to safety. It’s true to say that the successful automation of an operation can significantly reduce the health and safety risks which are often associated with the mining industry.
When companies are exploring automation or remote operation of a particular machine, they need to feel confident that the technology can emulate the actions of the operator in a safe and productive manner. Recent technological breakthroughs have been centred upon machine vision and intelligence. Most notably, the sophistication of microprocessors has advanced by many orders of magnitude and have transformed modern society. In the mining industry in particular, they are at the heart of the smart sensors we see in the market today. Such power and speed in computing allows these sensors to mimic the human brain and therefore replicate the intelligence required for the machines that are in operation – the driverless trucks being one of many noteworthy examples.
Furthermore, it wasn’t so long ago that INS devices, traditionally used in missile navigation, were highly classified devices which required permission from the U.S Department of Defense. These systems which contain processing signals enabling it to track the position and orientation of a device are now much more widely available. Underground mining automation systems such as longwall shearers for example are benefiting from such technology where there is no possibility of receiving satellite reception.
Another essential aspect which did not exist 20 years ago is the data infrastructure which allows companies to monitor and gather important machine parameters regarding the performance and maintenance diagnostics of their machines. Advances in digital communications have enabled 3G and other networks with significant bandwidth to be built over substantial areas in remote locations.
BMT recently conducted a project in partnership with the Australian Coal Association Research Program (ACARP) to look at improving the performance of automatically-controlled slewing reclaimers. The aim of the project was to develop a pre-emptive control technology to enable significantly higher average reclaim rates to be achieved.
The benefits of automatically controlling stockyard machines are now well known and accepted, and there are a number of existing machines in Australia and worldwide that are currently operating under automatic control. While automatic control of stackers is relatively straightforward, the most commonly used reclaimer, which employs a slewing bucketwheel, presents a more difficult challenge.
Most current automatic control techniques used on slew reclaimers are limited by the absence of accurate information about the stockpile shape. As a result, they often spend a significant amount of time outside the pile, and have difficulty maintaining constant reclaim rate within the pile. As a first step in this investigation, a technology demonstration trial was conducted, where the laser scanning (LiDAR) system was tested on an operating stacker reclaimer. In the initial trials, the reclaimer was driven in automatic mode, using its existing reclaim control systems and strategies, in their normal operational configuration. The laser test system was used concurrently to calculate volumetric reclaim rates dynamically to assess how effective existing control systems are in maintaining reasonably constant rates.
Comparison of throughput rates from the laser-based test system with the reclaimer’s belt weigher demonstrated reasonable consistency. Following completion of the initial technology demonstration phase, a number of additional tests were conducted to assess the potential gains available through application of the proposed improved control technology. Based on the results of this investigation, it is clear that the opportunity exists to increase average reclaim rates on this reclaimer by at least 20% to 30%, and that this level of improved performance should be achievable through application of the proposed laser scanning technology in combination with a pre-emptive control strategy. A key message here is that in order for an automated system to achieve performance equivalent to manual operation, it is necessary that the system mimics the way a good operator controls the machine.
Encouragingly, the industry is adapting accordingly and there are very few technical hurdles that need to be overcome. However, companies need to be mindful of the challenges associated with implementing these technologies as the technical risks can be quite intense and significant. Setting up centralised operations which control the automated trucks operating in the Pilbara region in Western Australia and also monitor the loading facilities at the ports is no mean feat - it requires huge infrastructure investment and a complete understanding of the technology requirements.
Let’s not forget that some of these machines can cost many tens of millions of dollars (AUD). It’s for this reason that many companies see automation as a progressive development to help minimise the potential, technical risks. If not duly considered, assets could be destroyed or worse still personnel could be exposed to a hazardous working environment increasing the risk of accidents occurring.
Remote operation can often be seen as a step towards complete automation. This is certainly relevant in parts of the industry where the human operator is performing extremely complex tasks in a highly intense environment. An operator of a large rope shovel is one such example where the brain has to work very hard and rapidly make multiple decisions in order to keep digging in the correct place and safely unload the product into the trucks that sit alongside.
However, companies must appreciate that the process towards achieving effective remote operation is much more complex than simply replacing what the operator sees with the installation of a number of cameras. If you simply provide remote vision, you lose the 3D location and motion/vibration perceptions that an operator relies on to do his job. To help resolve this challenge techniques similar to those used in the gaming and simulation world are being explored with the objective of creating a virtual model of the machine in its operating environment.
Although the main driver for automation and remote operation is safety, it’s important to note that there are also opportunities for improved productivity. Monitoring systems such as BMT’s PULSE TerraMetrix provide dragline and shovel operators with a balanced view of machine production and health in real time. This capability is relevant to production, maintenance and operator training staff in achieving demanding production and maintenance schedules. Real time data is provided to the machine operator in a concise relevant format, allowing strategic operating practices to be implemented. Such practices have proven to increase overall productivity and reduce machine maintenance.
Companies must not underestimate the complexities surrounding the implementation of automated or remote operations. Thinking through every aspect of the tasks the operator performs and what it is you need your automated or remote system to mimic is not always entirely clear and it’s important that the industry continues to work together to help overcome some of the technical and operational challenges which in some instances, have yet to be identified.
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