534 3.3 Integration Of Geological Context And Real-Time Drilling Feedback A recurring limitation in current systems is the inadequate integration of geological information with drilling telemetry. Real-time lithology recognition and hardness estimation remain largely manual or based on delayed post-processing. Recent works demonstrate that combining drilling telemetry with downhole sensors and geophysical logs improves real-time lithology classification using ensemble learning techniques. These integrated models enable dynamic adjustments to drilling parameters, reduce non-productive time, and improve fragmentation outcomes. 3.4 Human-Machine Coordination Human cognitive processes to avoid automation complacency and maintain situational awareness. In drilling contexts, this translates to interactive visualization, explainable AI outputs, and intuitive interfaces that guide operators without obscuring underlying uncertainties. Understanding how digital tools influence operator behavior, training, and performance remains underexplored. 4. PROPOSED DIGITAL DRILLING ARCHITECTURE To overcome interoperability, governance, and analytical constraints identified in previous assessments of drilling digitalization, this work proposes a modular, vendor-neutral, and scalable digital architecture specifically designed for large-scale production drilling environments. The framework is conceived to operate under the structural realities of open-pit mining: heterogeneous multi-brand drilling fleets, highly mobile assets, harsh environmental conditions, and variable wireless connectivity. The architecture is structured into functional layers that deliberately decouple data acquisition, transmission, storage, and analytics. This layered design ensures operational resilience, technological flexibility, and long-term scalability. 4.1 Source-Level Data Acquisition The first layer focuses on direct acquisition of high-resolution operational variables from programmable control systems embedded in each drilling unit. These variables include penetration rate, rotational torque, thrust force, air pressure, hole depth, and drilling cycle time. To address the complexity of heterogeneous PLC ecosystems, industrial open communication standards are employed to translate proprietary control signals into a unified and standardized data structure. By abstracting manufacturer-specific protocols into an interoperable data model, the system eliminates vendor lock-in and enables cross-platform compatibility across multi-brand fleets. This approach establishes a foundational layer of structured operational intelligence independent of equipment origin.
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