Advancing underground autonomy

New and enhanced features of the ORB Live / Autonomous module take autonomous dispatch and real-time dynamic cave management to the next level and pave the way for fully autonomous underground operations.

In the evolving world of underground mining's push for greater automation, the ORB Live / Autonomous module has become an indispensable tool to help manage the dynamic nature of complex block caving environments. ORB aligns production with strategic goals to maximize draw compliance and productivity by optimizing the dispatch of equipment in real-time.

"ORB’s goal is to ensure that dispatch decisions are finely tuned to the constantly evolving cave conditions, all while adhering to critical mining constraints," explains Steven Donaldson, ORB Technical Director at Deswik. He highlights how this approach significantly boosts equipment and personnel productivity through mathematically optimized draw management.

While ORB Live functions as a real-time data collection system, drawing inputs from various sources to create an accurate representation of the cave state, ORB Autonomous enables mine operators to manage draw compliance and provide real-time control for dispatch decisions autonomously through a unified platform.

The incorporation of short interval control into daily plans signifies a departure from the constraints of rigid daily schedules and key performance indicators (KPIs). Rather, workers are now able to maintain sustained productivity throughout their entire shift, fostering a more flexible and adaptive approach to real-time draw management strategies. In addition, "ORB contributes to advancing the maturity level of automation by treating the equipment in the cave as a unified team rather than individual components,” Steven Donaldson highlights a key feature, which marks a significant step in climbing the automation maturity scale.

These key capabilities of the ORB Live / Autonomous module have enabled clients to advance towards fully autonomous systems, moving from Level 3 and 4 to a Level 5 in the GMG Mining Automation Maturity Model. “Essentially, we are now able to autonomously dispatch to manual as well as to autonomous loaders in real-time” Donaldson concludes.

The addition of new features has expanded the application of ORB into more areas of underground block cave and sub-level cave mining environments since its initial launch over a decade ago.

ORB has further enhanced its capability to manage more complex materials handling systems. The autonomous module can now include truck dispatch, broadening its application from just loaders to also encompass trucks, including autonomous vehicles, in the dispatch process.

This enhancement integrates trucks more comprehensively into the system, facilitating a more seamless and efficient dispatch operation for a wide variety of haulage layouts. Furthermore, ORB can move beyond pre-determined haulage routes to prescribe optimal route selections based on the mining constraints and location statuses in real-time.

In addition to modeling trucks, ORB can now consider ore passes for both load and haul activities. Managing ore passes is streamlined with ORB Live, providing insights into the availability and contents of each ore pass. The ORB Autonomous system takes charge of determining which trucks and loaders tip into and load from ore passes, ensuring an efficient and responsive approach to materials handling in underground mining operations.

ORB's event handling has been significantly enhanced to better facilitate complex workflows in managing cave states. The event management system has been updated to include a broader spectrum of event types, notification options and details of location, resources, and statuses. As a result, users gain increased flexibility and control over their mining operations.

An example to illustrate the versatility of this enhancement is where material can be visually identified based on the condition of draw points. This involves manual inspection and input of material data into the system, facilitating surveys on tablet devices to assess the quality of material at specific draw points. Unlike traditional systems that react only when a draw point is blocked, this feature introduces a nuanced, rules-based approach, such as identifying a "wet" draw point, prompting the system to decide the appropriate type of equipment for the task at hand – and dispatch it autonomously.

ORB has undergone an overhaul of its user interface which provides users with more customization options and quality-of-life features. Customers are now able to manage widgets, viewports and asset information across multiple screens to suit the operational needs of the mine.

Previously constrained to block caving layouts, ORB has evolved to be more generic, allowing users to upload custom maps which may span over multiple mine levels. This enhanced flexibility includes being able to support additional types of equipment such as jumbos, bolters and spraymecs to provide a more comprehensive overview of operations. This evolution marks a significant stride towards a more versatile and user-friendly experience, aligning seamlessly with the diverse requirements of modern underground mining operations.

With these new features, the ORB Live / Autonomous module is contributing to pushing the boundaries of underground automation towards full autonomy.

The long-term vision is to extend the application of ORB to all hard-rock underground mining methods, with the initial focus directed towards sub-level caving environments. While block caving has seen successful implementation due to its comparatively stable environmental factors and good data maturity, the leap into sub-level caving introduces a new level of intricacy.

A pioneering client has initiated this process, prompting operational adjustments to accommodate the unique challenges. In this sub-level caving operation, ORB is currently applied to help visualize the draw strategy and manage production at the cave front. It is also now responsible for the scheduling and dispatch of production loaders in some mining areas.

Despite the complex challenges that still need to be overcome to achieve comparable levels of decision automation, investing the time and innovation required for transformation will undoubtedly bear the fruit of making this vision a reality.