Sponsored CIM Connect Video: Hexagon says fragmented systems blunt mining AI

Key Concepts

• Connected Context: The integration of data across the entire mining value chain to overcome fragmented systems.
• Ore-to-Value: A methodology focused on optimizing the extraction of an asset from the ground to ensure maximum marketable value.
• Living Digital Twin: A dynamic model that utilizes continuous feedback loops to adjust operational plans in real-time based on current site conditions.
• Orchestration Layer: The technological framework that synchronizes upstream mining activities (drilling, blasting, hauling) with the constraints of the processing plant.
• Expertise Gap: The industry challenge caused by the retirement of long-tenured professionals and the difficulty in replacing their specialized knowledge.

---

1. The Limitations of Automation

Dave Gothard argues that while automation addresses the labor shortage regarding machine operation, it fails to solve the industry's broader "expertise gap." As veteran workers retire, the industry loses critical institutional knowledge. Hexagon’s strategy is to supplement automation with "smarter solutions" that provide the necessary context to help the incoming, less-experienced workforce make informed decisions.

2. The "Ore-to-Value" Framework

"Ore-to-value" is defined as the process of ensuring that the geological asset identified in the ground is extracted and processed in a way that realizes its full economic potential.

• The Challenge: Mining companies often struggle to bridge the gap between initial resource estimation and the final saleable commodity.
• The Solution: By connecting workflows across the entire value chain, operators can ensure that the material extracted is the most profitable, rather than simply focusing on volume or "high-grading" (extracting only the highest-grade ore to meet short-term targets, which can destroy long-term asset value).

3. Living Digital Twins vs. Traditional Models

Traditional digital models are often static and fail when operational realities deviate from the plan.

• The Feedback Loop: A "Living Digital Twin" incorporates a continuous feedback loop. If a disruption occurs (e.g., equipment failure or geological surprise), the model updates immediately.
• Strategic Shift: Instead of asking, "How do we get back on the original plan?" (which often leads to value-destroying decisions), the system asks, "What actions today preserve the long-term Net Present Value (NPV) of the asset?"
• Operational Horizon: This allows for a rolling 14-day plan that is always informed by current, real-world conditions.

4. AI Adoption and Human Context

Gothard highlights two primary barriers to AI adoption in mining:

• Cultural Conservatism: The industry is inherently risk-averse, particularly regarding multi-million or billion-dollar capital investments.
• The Role of AI: Gothard emphasizes that AI should not replace human decision-making for major capital bets. Instead, AI should be used to "structure" the decision-making process, providing the human operator with the data context required to make the final call.
• Future-Proofing: Hexagon is investing in university partnerships to cultivate "digital natives" who can bridge the gap between traditional mining expertise and modern AI-driven workflows.

5. Connecting the Pit to the Plant

The processing plant is identified as the primary bottleneck and the largest capital expense in a mine.

• Constraint-Based Planning: Because the plant is designed for specific material parameters (grade, friability), the entire upstream sequence—drilling, blasting, and hauling—must be orchestrated to feed the plant the optimal material at the right time.
• Orchestration: This requires a holistic view where the plant’s requirements dictate the activities in the pit, ensuring that throughput and recovery rates are maximized.

---

Synthesis and Conclusion

The core takeaway from the discussion is that the mining industry’s failure to fully leverage AI and autonomy stems from fragmentation. Technology is currently deployed in silos, preventing a unified view of the value chain. By implementing a "living" digital infrastructure that connects the pit to the plant, mining companies can move beyond reactive, short-term planning. The ultimate goal is to transition from a model of "getting back on plan" to a model of "maximizing long-term NPV," supported by AI-structured insights that empower, rather than replace, human expertise.