203 5. BACKGROUND Mining productivity depends on multiple factors including equipment reliability, operational planning, infrastructure, and human resources. While maintenance strategies aim to improve mechanical availability, productivity improvements require that operational conditions allow equipment to be effectively used (Bernaola, 2012). Studies on underground mining operations have shown that reducing unproductive times significantly improves equipment utilization and operational efficiency (Apaza, 2017; Martínez, 2016). Long-hole drilling is a highly mechanized mining method used in sublevel stoping operations, where long holes are drilled toward the orebody and blasted to extract large volumes of material. This method offers high productivity but depends strongly on continuous operational support, such as adequate ventilation, access to the work face, energy supply, and operator availability (Arniel et al., 2016). Time management is critical in drilling operations, as equipment performance is determined not only by mechanical failures but also by operational delays that reduce productive drilling time. Previous research has identified that operational delays, auxiliary equipment availability, and coordination inefficiencies are among the main factors affecting productivity in underground mining operations (Gómez, 2017). 6. CONCEPTUAL FRAMEWORK Mechanical availability is defined as the percentage of scheduled time during which the equipment is mechanically capable of operating. Utilization is defined as the percentage of available time during which the equipment is effectively operating in productive drilling activities. Operational elasticity represents the sensitivity of utilization to changes in availability and can be expressed as: !"#$%&'&%( = %∆,%&"&-#%&./ %∆01#&"#2&"&%( ( 1 ) In regression-based terms, operational elasticity can be estimated as: !"#$%&'&%( = 3 ∙ 5766 ( 2 ) Where: ● β is the slope coefficient obtained from linear regression. ● X̄ is the average mechanical availability. ● Ȳ is the average utilization. A negative elasticity value indicates that increases in availability are not translated into proportional increases in utilization, suggesting that operational constraints dominate performance. 7. METHODOLOGY This research follows a quantitative analytical approach based on the use of historical operational records. The methodology consisted of integrating operational databases, calculating KPIs, applying
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