2344 • Persistence of events despite the application of active breaks. • Occurrence of events in critical time windows. These findings highlight that, while the system effectively detects the manifestation of the event, it does not provide an explicit reading of the accumulated state of the system or the probability of occurrence of future high-energy events, reinforcing the need for an anticipatory approach at the systemic level. 2. PROBLEM DEFINITION Modern mining continues to manage risk primarily by measuring past events, such as incidents, deviations, operational failures, critical exposures, or performance losses. While traditional statistical models allow for the analysis of historical trends and the estimation of probabilities, these approaches have structural limitations when dealing with complex, dynamic, and constantly evolving systems. In particular, three main limitations are identified: 2.1 Dependence on the past Conventional models require significant volumes of historical data for calibration, which do not always represent emerging conditions, unprecedented configurations, or accelerated changes in operating systems. 2.2 Exclusion of unobservable states Many critical system configurations never materialize as reportable incidents or events. However, these configurations may contain significant operational stresses that increase the potential for high-energy events, remaining invisible to traditional indicators. 2.3 Limited anticipatory capacity Most indicators considered “predictive” rely on indirect proxies, such as behavioral reports, inspections, or observed unsafe conditions, which offer limited and, in many cases, late anticipation of dangerous system states. As a result, risk management tends to maintain a retrospective and reactive character, with low sensitivity to detect emerging states or unprecedented combinations of variables that have not yet been previously experienced. In the specific area of fatigue and drowsiness, current systems allow for the real-time identification of fatigued operators; however, they have structural limitations in anticipating systemic configurations prior to the event's manifestation. The recurrence of alerts, their concentration by shift, route, or specific periods, and the persistence of events despite the implementation of active breaks, demonstrate that fatigue must be addressed as an emergent phenomenon of the work system, and not solely as an individual condition. In this context, the Quantum Potential Index Applied to Fatigue (QPIFAT) proposes to incorporate unobserved potential states within a formal structure, with the purpose of anticipating possible futures before their materialization, thus complementing traditional detection and control approaches. 3. STATE OF THE ART Globally, research in predictive mining has focused on: • Machine learning models based on supervised and historical training. • Predictive maintenance systems. • Equipment reliability models. • Bayesian probability applied to security events. • Discrete event simulation models. • Predictive indicators derived from human behavior.
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