323 4.3. Safety Performance and Risk Reduction Outcomes Maintenance is fundamentally a risk control activity where Risk = Consequence x Probability. The digital transformation contributes to safety by: • Early Intervention: Identifying developing issues "hours to months" before they lead to catastrophic or imminent asset failure. Figure 14 - Success case vibrations monitoring • Reduced Field Exposure: By diagnosing equipment health remotely, the need for traditional on-site support and physical audits by specialists is reduced, thereby lowering the exposure of personnel to hazardous mining environments.(Su & Zabilski, 2022) • Predictive Insights: Moving from reactive (Mining 1.0) to predictive/prognostic maintenance (Mining 4.0) allows for safer, planned interventions rather than emergency repairs. Figure 15 - Historical avoided cost 4.4. AI and Machine Learning (ML) Integration The transition from Mining 3.0 to Mining 4.0 demands a shift from "threshold-based alarms" to "modelbased anomaly detection."(Chaowasakoo et al., 2017) • Anomaly Detection: Utilizing the Komatsu Analytics Platform (KMAP) and high-resolution telemetry (1 to 10Hz), unsupervised learning algorithms will be deployed to identify subtle deviations in the P-F Interval (Potential failure to Functional failure). • Prognostic Modeling: Future research focuses on correlating multi-variable data—such as payload, incline, and temperature—with the structural integrity of major components (engines, transmissions). This allows for a Remaining Useful Life (RUL) estimation rather than relying on fixed hour-based intervals.
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