● no sustained upward trend is observed over time, and ● Latent and human variables remain decoupled from environmental conditions. In these cases, the system may experience isolated fatigue alerts without these representing a dangerous systemic configuration. “For interpretative purposes, preliminary threshold bands were defined and discussed in Section 12” 7. WHAT RADICALLY CHANGES WITH QPIFAT + OAS? Aspect OAS today OAS + QPIFAT Approach Reagent Predictive Analysis unit Operator System + shifts + routes Horizon Minutes Days / weeks Decision Pause Shift redesign, staffing, routes Strategic value Complian ce Anticipation of SIF-P (Potential Fatalities and Serious Injuries) Aspect Traditional Approach QPIFAT Horizon Reagent Anticipatory Analysis unit Operator System Time of intervention Post-alarm Pre-alarm 8. METHODOLOGY Although the focus is conceptual at this stage, it follows a clear procedural sequence that allows for its consistent application in comparable operational contexts. The methodology consists of the following stages: 8.1.Definition of data sources Existing operational data streams that will serve as inputs for the Q-SiD framework are identified and selected. These sources include, but are not limited to, outputs from fatigue monitoring systems, operational exposure indicators, work-rest patterns, and contextual operational parameters already available within the organization. No additional sensors or new data acquisition systems are required. 8.2.Selection and normalization of variables Key precursor variables associated with fatigue and exposure to high-potential energy are selected using expert judgment, ensuring their alignment with critical risk pathways. To allow comparability between heterogeneous variables, all are normalized to a common scale, enabling their integration within a single systemic representation. 10
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