Digging deeper with edge: How mining companies reap the benefits of edge computing

The mining industry is undergoing a massive transformation to rethink how all aspects of the lifecycle of a mine is implemented. The mine of the future must be fossil-free, safe for workers, and environmentally sustainable in harmony with surrounding communities.

Forward looking digital initiatives are ongoing across exploration, discovery, development, operation and closure of mines. There are a set of key themes that are relevant across including increasing production autonomy, improved safety, reducing the environmental impact, all the while providing more efficient extraction and processing.

To deliver on this vision, mining operators must consider their options for deeper automation of their production control as well as the ability to efficiently collect and analyze data for the purposes of e.g. proactive preventive equipment maintenance, safety monitoring and remote inspections. They do this by carefully picking a strategic mix of in-mine infrastructure and modern applications.

Keep reading: What is distributed edge application orchestration?

All of these tasks require a well-defined edge-to-cloud strategy to:

• Facilitate efficient and safe placement of compute capabilities for e.g. AI/ML workloads where they provide the most value.
• Allow data to move seamlessly between from the point of capture to where the result of multi-stage analysis is delivered and consumed.
• Support a hybrid strategy of the placement of operations teams and Remote Operations Centers (ROCs) to best utilize the plant and people while maintaining non-stop operations in potentially adverse physical conditions.

The mine as the edge in edge computing

The concept of edge computing – centered on the ability to host applications, and collect data in remote locations and close to the production environment – will be at the heart of the push towards the mine of the future.

Combining edge computing infrastructure in the mines with a modernized application stack to leverage the learnings of cloud computing in terms of people, processes and tools promises to further reduce cost and improve efficiencies.

Recent examples of rapidly developing types of applications include:

• Remote inspections using cameras and other sensors in the mines combined with locally hosted machine learning applications to simplify the process and significantly reduce (or remove) the need for physical inspections
• Proactive and preventive maintenance by analyzing data from cameras as well as noise, light, vibration or LiDAR sensors in the mines with locally hosted applications to detect and avoid potential catastrophic faults as well as the basis for proactive maintenance of aging equipment.
• Safety monitoring based on e.g. vibration, fire- and toxic gas detection combined with in-mine applications for demand-based personell and vehicle routing during emergency situations.
• Applications enabling self-driving vehicles for operations in dangerous or otherwise hostile environments.

All these solutions are based on the combination of distributed and resilient compute capabilites in the mines, and being able to leverage modern application stacks to provide the fundamental cost model and agility needed to rapidly addressing the top level pressing issues. And it has the ability do so in a way that allows operators to seamlessly migrate away from their current closed and partially human-driven processes and approaches.

Keep reading: “I just want to run my containers”

Conclusion

Edge computing has the potential to allow the mining industry to address the current challenges around safe, efficient and sustainable production. This can be done while reducing cost by reusing the learnings of the IT-industry as a whole.

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