By Marco Capazario, business unit lead and manager at Britehouse
One of the biggest challenges facing mining executives today is the critical visibility gap that stems from siloed operational technology (OT) and information technology (IT) systems, with implications that directly impact operations, production output and, ultimately, the bottom line.
Without seamless integration, mining operations teams struggle with fragmented data, while executives lack real-time insights. The resultant blind spots in production performance, asset health, and health and safety can impact critical decisions around capital expenditure, mining outputs, input costs and operational risks.
The cost of this visibility deficit is substantial: compliance risks, unplanned downtime due to reactive maintenance, suboptimal resource allocation, and missed opportunities to optimise production throughput.
In an industry where margins are increasingly pressured by commodity price volatility, regulatory complexity, and rising operational costs, this lack of integrated data-driven intelligence is unsustainable.
The converged data solution
The solution to these challenges is IT/OT convergence via a cloud-native agentic integration platform, like SnapLogic, that can connect a mining company’s enterprise resource planning (ERP) system with an operational intelligence solution, like Aveva Mining Intelligence, to establish a unified data layer that breaks down information silos and delivers enterprise-wide visibility.
When implemented correctly, this integration architecture enables the seamless, real-time flow of data, delivering production data, equipment performance metrics, and inventory levels through centralised dashboards, creating a single source of truth that spans from the pit to the boardroom.
Enhanced operational visibility and efficiency
A unified data layer that converges IT systems, such as ERP, customer relationship management (CRM), asset management, and Business Intelligence (BI), with OT systems – supervisory control and data acquisition (SCADA), Programmable Logic Controllers (PLCs), and Electronic Control Unit (ECU) downloads – gives mine operators unprecedented visibility across the operation.
In the plant environment, an ERP system tracks raw materials into the plant, where a SCADA system picks up the material and tracks it through the processing stage, before the ERP system tracks the output to delivery. The challenge is seamlessly tracking all inputs through to outputs, which only becomes possible by integrating these two ecosystems together.
Real-time equipment monitoring through IoT sensors empowers operations teams to work with real-time data that supports proactive decision-making.
These data-driven insights help optimise production by identifying bottlenecks instantly, optimising haulage routes dynamically, and adjusting production plans based on actual equipment availability and performance trends rather than backward-looking, outdated reports.
This visibility translates directly to operational efficiency gains that deliver measurable improvements in overall equipment effectiveness and production throughput without proportional increases in operating costs.
Predictive maintenance and asset optimisation
Data integration also creates a foundation for transforming maintenance from a cost centre into a strategic advantage.
By connecting ERP asset registers with Aveva’s operational monitoring, mine operators gain complete asset visibility across the mining value chain.
Integrating sensor data, such as oil temperature, vibration, operating temperature, and particle count with lab analysis data enables sophisticated predictive maintenance programs and early failure detection outside the conventional service cycle.
The ability to monitor factors such as fuel dilution and dust ingress, and the ability to predict component failure before these escalate – based on actual usage patterns, operating conditions and equipment health indicators – helps to extend asset life, increase mean time between failures (MTBF) and reduce costly catastrophic failures that can cause unplanned extended downtime, and optimises maintenance resource deployment.
This proactive detection through IT/OT convergence and the resultant predictive maintenance can mitigate the R1-million cost per day associated with downtime for repairs to a R1.4-million engine.
Furthermore, fewer emergency breakdowns reduce overtime labour, express part shipments and unplanned contractor costs.
Safety and risk reduction
Critically, unified data visibility directly enhances health and safety outcomes by pre-empting potential risks and hazards. Real-time alerts on overheating, pressure spikes, or structural failures in drill rigs or dump trucks reduce operator risk.
Pre-shift inspections logged in mobile devices automatically update ERP records and trigger alerts if equipment operating outside safe parameters attempts to enter production service.
When incidents do occur, integrated data enables rapid root cause analysis by correlating equipment telemetry, operator actions, environmental conditions and maintenance history from a single platform. These insights inform preventive measures that reduce incident recurrence rates.
Integrating IT systems and IoT sensors supports dust monitoring and ensures compliance with air-quality and emissions standards.
The ability to demonstrate comprehensive safety compliance through integrated and consolidated audit trails for safety inspections, environmental monitoring, and statutory reporting also strengthens regulatory relationships and reduces exposure to penalties.
Cost reduction
Integrated data enables mining companies to identify and eliminate cost inefficiencies that remain hidden in siloed systems.
When Aveva Mining Intelligence can access real-time procurement data, inventory levels and supplier performance metrics from an ERP solution, supply chain optimisation becomes proactive rather than reactive. Excess inventory carrying costs decreases, stockouts that halt production are prevented, and procurement decisions are informed by actual consumption patterns and predictive demand modelling.
Beyond the operational advantages, integrated mining data paves the way for mine operators to implement and leverage the latest AI-enabled capabilities. An integrated data architecture ensures AI models work with complete, contextual information spanning operational and business systems, which improves predictability models.
AI can correlate oil contamination, ECU logs, and vibration signatures to automate fault detection and make real-time recommendations for simple corrective actions to foremen. AI then monitors the effectiveness of any remedial action at a management level.
Machine learning models trained on historical integrated data can forecast production output with greater accuracy, enabling better financial planning and commitment management to customers, while the real-time replication of mining equipment, such as rigs, haulers and conveyors create digital twins for simulation and optimisation to further streamline operations.
Furthermore, scalable architecture prepares operations for future tech adoption, such as 5G underground communications, AI bots and autonomous haulage.
Strategic and competitive advantage
IT/OT convergence in mining turns operational data into a strategic asset by shifting operations from reactive to predictive, reduces downtime and safety risks, maximises asset life, and creates a direct line between sensor data and business decisions, translating into measurable financial return on investment (ROI).
When enhanced with AI-driven analytics and deployed with the guidance of an experienced, qualified systems integrator with specialised expertise, this architecture delivers measurable improvements in operational efficiency, cost management, asset optimisation and safety performance.
In an industry where operational excellence increasingly differentiates market leaders from laggards, unified data visibility has become a strategic imperative. The companies that act decisively to break down data silos and establish AI-ready integration architectures will define the next era of mining excellence.
 Marco Capazario, business unit lead and manager at Britehouse. Supplied by Britehouse |
Introducing the author:
Marco Capazario is a business and technology leader specialising in industrial IoT, AI-driven predictive maintenance and digital transformation across the mining, heavy equipment and energy sectors. As the business unit lead at Britehouse, he drives innovation through connected sensor systems, edge computing and AI-enabled analytics that improve asset reliability, reduce downtime, and enhance operational visibility. Capazario has led numerous digital initiatives across South African mining operations, integrating oil condition monitoring, telematics and machine-vision technologies into unified platforms such as Atajo FX and Atajo OnEdge. His work bridges the gap between OT and IT, helping enterprises unlock real-time insights, sustainability gains and measurable ROI through data-driven intelligence. |