2.5. Human Factors and Change Management Integration The methodology explicitly integrates human factors and changes management as structural components of the implementation process. The evolution of the operator’s role from manual control to supervisory and exception-based management requires the development of new competencies and a gradual adaptation to new modes of operation.(Iversen et al., 2013b) Training activities were designed incrementally and aligned with each autonomy level, complemented by on-site support, continuous feedback, and procedural refinement. In parallel, change management practices were implemented to ensure alignment across operations, maintenance, safety, and technical teams, reinforcing acceptance of the new operating model. The transition also required adaptation to a new digital operating environment within the mobile control station. Operators were trained to interact with integrated visualization systems, including multi-camera feeds installed on the drill, centralized fleet management interfaces, real-time machine condition monitoring dashboards, and digital drilling pattern loading tools. These systems enabled situational awareness, performance tracking, and remote intervention capabilities from a physically separated environment. Software-based alert systems, including operational alarms and fatigue-related notifications, were incorporated to support supervisory control and maintain operator attention during remote operation phases. The integration of these tools redefined the operator’s function from direct equipment manipulation to system supervision, exception management, and decision-making based on real-time data streams. This synchronized integration of technological tools, human factors training, and structured change management ensured that the transition toward tele-operation and supervised autonomy was both technically stable and organizationally sustainable. 2.6. Methodological Validation Criteria Progression between autonomy stages was governed by a structured, data-driven validation framework based on direct comparative analysis between conventional manual drilling and Auto Pilot-assisted operation. Escalation was authorized only after sustained operational stability and performance consistency were demonstrated under real production conditions. Operational validation relied on time-derived production indicators extracted from 100-hole drilling grid execution records and shift-level performance logs. The defined KPIs enabled objective comparison between manual and Auto Pilot operating modes: • Hole Change Time (T_change): Time required to reposition between holes (minutes/hole) • Drilling Time (T_drill): Active drilling duration per hole (minutes/hole) • Overdrilling Time (T_over): Additional drilling beyond planned depth (minutes/hole) • Re-drilling Time (T_re): Corrective drilling due to deviation (minutes/hole) The aggregated grid-level indicator was defined as: • Total Grid Time (T_grid): Total execution time for a 100-hole drilling grid (minutes/grid) = ℎ + + +
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