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Artificial intelligence, machine learning, and the pivotal role of the next generation of engineers were the key issues raised at the recent annual symposium hosted by the Zimbabwe National Institute of Rock Engineering (ZINIRE) at the Elephant Hills Hotel in Victoria Falls on Friday, Mining Zimbabwe can report.
By Rudairo Mapuranga
The event, which served as a critical nexus for industry veterans, suppliers, and academia, was overwhelmingly defined by a palpable shift towards digitalisation, driven by the innovative contributions of young professionals.
The consensus among leadership and attendees was clear: the future of Zimbabwean mining is being written in code and algorithms, and it is the country’s emerging talent that is leading this technological revolution to solve perennial challenges like rock support design and fall-of-ground incidents.
Speaking to Mining Zimbabwe on the sidelines of the symposium, ZINIRE President, Mr. Omberai Mandingaisa, set a tone of profound optimism and acknowledgement for the fresh perspectives brought to the fore and highlighted that the event marked a significant milestone in the industry’s ongoing evolution.
“The involvement of youngsters that are in college, that are our upcoming rock engineers and the future of the mining industry, has been exceptional,” stated Mandingaisa. “They have brought up so many presentations that have to do with applications of AI into rock support, applications of AI into the design of support systems and all the applications of new technology, new state-of-the-art equipment. This has come at a stage where the mining industry in Zimbabwe is being revolutionised.”
This sentiment underscores a strategic pivot. For an industry historically grounded in empirical methods and experience-based judgement, the enthusiastic embrace of data-driven technologies by students and young professionals signals a foundational change in how rock engineering challenges will be approached in the decades to come.
The Technical Imperative of AI and ML in Rock Engineering
The presentations delivered by the young professionals moved beyond theoretical discussion, delving into specific technical applications that are poised to enhance safety and efficiency. The core technical issues addressed revolved around several key areas:
AI-Powered Rock Mass Characterisation and Classification: Traditional methods like the Rock Mass Rating (RMR) or Q-system, while effective, involve a degree of subjectivity and are time-consuming. Engineers and service providers presented research on using convolutional neural networks (CNNs)—a class of deep learning algorithms—to analyse digital images and LiDAR point cloud data of rock faces. These systems can be trained to automatically identify discontinuities, joints, fractures, and rock types, calculating parameters such as roughness, persistence, and spacing with superhuman consistency and speed. This leads to a more objective, rapid, and continuous assessment of ground conditions, allowing for real-time adjustments to support plans.
Machine Learning for Predictive Analysis of Fall-of-Ground (FOG): This was a recurring and critical theme. Fall of ground remains a primary safety risk in underground mining. Presentations focused on using machine learning models for predictive maintenance and hazard forecasting. By feeding historical and real-time sensor data—from microseismic monitoring systems, stress meters, extensometers, and even drone-based photogrammetry—into algorithms like recurrent neural networks (RNNs) or support vector machines (SVMs), models can learn to identify subtle precursor patterns that human analysts might miss. These systems can then provide early warning signals of impending instability, predicting the probability of a FOG event with a significantly higher lead time, thereby enabling pre-emptive intervention and evacuation.
Optimisation of Support System Design: The design of ground support systems, including bolt patterns, shotcrete thickness, and cable bolt density, is a complex engineering problem influenced by a multitude of variables. Young professionals showcased work on using generative design algorithms and reinforcement learning. Instead of a single solution, AI can generate thousands of viable support design options based on desired outcomes (e.g., maximum safety factor, minimal material cost). The algorithm iteratively learns which combinations of parameters are most effective, optimising the design for both safety and economic efficiency in ways that were previously computationally prohibitive.
Interoperability and Data Standardisation – The Hidden Challenge: A more nuanced technical issue raised, often implicitly, was the challenge of data infrastructure. For AI/ML models to be effective, they require vast amounts of clean, standardised, and labelled data. A significant hurdle for the industry is the legacy of siloed data systems—where geological data, geotechnical monitoring data, and production data exist in separate formats and databases. Several presentations touched on the need for integrated data platforms and standardised protocols (akin to ISO standards for data exchange in mining) to fully unlock the potential of these advanced analytics tools. This highlights a sophisticated understanding among the youth that the technology is not just about the model itself, but the entire data ecosystem that supports it.
A Platform for Networking, Commerce, and Career Development
The symposium’s value extended beyond pure academia, serving as a vital commercial and professional nexus. Mr. Wayne Mudamburi, President of the Association of Junior Mining Professionals of Zimbabwe, emphasised this multifaceted role.
“The importance of ZINIRE is that it’s giving us a platform to actually network and it’s giving suppliers the platform to present their goods,” Mudamburi noted. “And then the mines can actually choose the best support elements that they want from these suppliers… it’s also giving the young rock engineers an opportunity to showcase themselves.”
This ecosystem is crucial for technological adoption. Suppliers showcasing state-of-the-art equipment—from smart bolts with embedded sensors to advanced drone-based monitoring solutions—provide the tangible tools that make the algorithms useful. The direct interaction between mines (the end-users), suppliers (the tool providers), and young engineers (the innovators and future operators) creates a powerful feedback loop that accelerates the practical implementation of research.
Shaping Minds and Aligning Futures
For the individual attendee, the impact was deeply personal and professional. Ope Muranda, Vice President of the Association of Junior Mining Professionals of Zimbabwe, articulated how the symposium is shaping the career trajectories of young professionals.
“As an individual, I’m gaining knowledge on how important the rock engineering department is to the mining industry as a whole,” Muranda said. “And also it’s helping me in shaping my future and shaping my direction, my thinking, my mind and also trying to align my goals to what I actually want.”
This speaks to the event’s role in not only disseminating knowledge but also in inspiring and focusing the ambitions of the next generation, ensuring the long-term health and innovation capacity of the field.
The Inevitable Future: Embracing the Digital Shift
Perhaps the most powerful takeaway, echoed by Muranda and many others, was the sense of inevitability and urgency surrounding this technological shift.
“The key takeaways from this was basically, there’s no way we are going to run away from artificial intelligence, machine learning, because the world, the future is artificial intelligence. The future in mining is going to be machine learning,” Muranda asserted. “So one way or the other, we need to, we are going to be forced to embrace and adopt machine learning and artificial intelligence… it’s about time that we take it serious and learn to implement it.”
This is no longer a question of if but how quickly the industry can adapt. The ZINIRE symposium demonstrated that Zimbabwe’s young rock engineers are not waiting to be forced; they are actively leading the charge, acquiring the skills, developing the applications, and building the networks necessary to ensure the domestic mining industry is not left behind but is instead at the forefront of this global transformation.
A Confluence of Talent and Technology
The annual ZINIRE symposium successfully illuminated the path forward for rock engineering in Zimbabwe. It was a powerful demonstration that the industry’s future is in capable hands. The fusion of youthful innovation with cutting-edge technology like AI and ML is creating a new paradigm for mine safety and efficiency.
As President Mandingaisa concluded, the goal is to “manage fall of ground” and other critical challenges. With the passion displayed by the young professionals and the powerful tools they are mastering, the symposium made it clear that this goal is increasingly within reach. The event was not merely a conference but a declaration: a new, digital era for Zimbabwean mining has begun, and its architects are already hard at work.
