1. INTRODUCTION The accelerating global demand for critical minerals, essential for electrification, renewable energy systems, and large-scale decarbonization, poses a structural challenge to the mining industry: how to expand production while simultaneously advancing efficiency, transparency, and environmental stewardship. Copper and other strategic minerals stand at the core of the energy transition. Yet increasing their supply is no longer driven solely by new discoveries or capital-intensive expansion projects. It increasingly depends on the industry’s capacity to reduce operational variability, enhance process predictability, and transform the vast volumes of operational data generated across the value chain into actionable intelligence. Within this context, production drilling constitutes one of the most influential technical leverage points in open-pit mining operations. Drilling performance directly shapes blast outcomes, determines rock fragmentation quality, influences downstream comminution energy intensity, and affects the overall stability and cost structure of the operation. Apparent minor deviations in parameters such as penetration rate, pulldown force, or torque can cascade through subsequent stages, amplifying energy consumption, decreasing predictability, and generating compounding efficiency losses across the production chain. Consequently, leading mining operations worldwide are intensifying their focus on productivity optimization, cost discipline, environmental performance, and operational resilience. Digital transformation has emerged as a strategic enabler of these objectives. Among all production processes, drilling holds strategic relevance because it fundamentally determines: • Blast design effectiveness • Fragmentation distribution and quality • Loading and hauling efficiency • Crusher throughput and specific energy consumption Despite its importance, drilling operations in many large-scale mines still rely on partial automation and manual reporting. Operational data generated by modern drilling rigs often remain underutilized due to: • Heterogeneous equipment manufacturers • Proprietary communication protocols • Lack of unified connectivity infrastructure • Limited interoperability between control and enterprise systems This paper presents a replicable model that transforms operational data into structured intelligence, strengthening productivity, predictability, and accountability in the supply of critical minerals in the face of current global challenges that transforms drilling into a connected, datadriven process aligned with Mining 4.0 principles. 2. STATE OF THE ART IN DIGITAL DRILLING The adoption of digital technologies in mining has advanced rapidly over the past decade, driven by the need to improve productivity, safety, energy efficiency, and sustainability. Within the
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