Latest News, 2022 News
Training for automation
As OEMs replace hydraulic levers with digital control systems, and the internet-of-things spreads relentlessly across the industry, mechanised mining has seen a proliferation of ‘smart’, semi-autonomous equipment, all of which seeks to reduce operator burden and enhance machine efficiency through technology. Increasingly, a new breed of operator is called for, individuals equally adept at programming machine automation via touchscreens as they are at barring a heading. In this seemingly contradictory, undeniably complex and as ever, hazardous environment, the case for high-fidelity simulator-based training is stronger than ever.
Traditional, manual operating proficiency is taken for granted, over and above which today’s operators are expected to focus on equipment set-up, operational monitoring and rapid intervention when the inevitably unexpected threatens to overwhelm automated routines. Full-mission simulators, such as ThoroughTec’s CYBERMINE products are uniquely positioned to help operators master both the basics as well as the extreme complexities of these systems and critically, learn when and how to intervene when things go wrong.
Another growth area for simulation is the virtualisation of training for non-line-of-sight or tele-remote mining applications. As mines seek to remove operators from hazardous operating areas, they increasingly turn to remotely-operated systems. While delivering huge safety benefits, the difficulty of effectively operating such systems invariably threatens mine productivity and operating costs.
Training may seem an obvious solution, but the scarcity and operational complexity of these systems virtually precludes the use of actual equipment for training purposes. Simulator-based training becomes essential and actually offers many benefits otherwise denied anyone attempting to train via alternative methods. Remarkably, given the realism of modern full-mission simulators, the differences between remotely operating a real vs a virtual machine are almost indistinguishable and consequently, skills retention and transfer to live operations is exceptionally high.
A digital cohesive mine training department
Traditionally mine training departments have been beset by a number of challenges, ranging from the wide-array and incompatibility of training methods and tools to excessive reliance on paper-based assessments, record keeping and organisation. Learning Management Systems have historically been used to some effect, but their benefit has been confined to the e-learning environment, and consequently their usefulness across the broader sweep of mine training systems and processes has been very limited.
To address this problem, ThoroughTec has developed the Workforce Excellence Training Management System (WX TMS), the world’s only, dedicated, mining training management system. A cloud-based, enterprise level software platform specifically engineered to cater for ANY type of training in the mining context. WX TMS is the cornerstone of the ThoroughTec’s Workforce Excellence eco-system, digitising and centralising the creation, planning, control, reporting and record keeping of ANY and ALL mine training activities, irrespective of subject, method or content.
While naturally optimised for use with ThoroughTec’s CYBERMINE range of products, the system is both technology and process agnostic, allowing it to accommodate virtually any mine training context or requirement. Such a system acts as the training department’s central nervous system, cohesively linking everything from curriculum development, course planning, and activity and resource scheduling to operator record-keeping and certification. Every type of training from classroom theory, e-learning systems and VR pre-trip testing to full-mission simulators and even live, in-pit training and evaluation is catered for, all the while providing near-real-time oversight to stakeholders throughout the organisational spectrum. The power and potential of such a tool is hard to express and there is simply nothing else like it.
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