318 Figure 7. Stages of the REM model 2.1. REM Data Management and Acquisition • Ensure that monitored equipment sends reliable, continuous, and correctly processed data to REM ecosystem platforms. • Equipment connectivity: Validation of signals, telemetry, gateways, transmission protocols and communications status.(Aguirre-Jofré et al., 2021) • REM Data Processing: Normalization, filtering, validation and structuring of signals from sensors, ECUs, electronic modules and on-board systems.(Zhang et al., 2020) • Applications and Servers (REM Platforms): Ad-Hoc Trending, Data Lake, Application Servers, APIs, and Ingestion Engines.(Leung et al., 2025) 2.2. Information Analysis and Fault Diagnosis (REM Analytics) Detect anomalous behavior, diagnose potential failures, and assess the operational health of assets. • Fault detection: Use of REM's own algorithms, business rules, thresholds, and trend models to identify deviations. • Technical Diagnosis: Analysis led by the REM/RHM Engineer and validated with Specialist Engineers to confirm root cause and operational risk. • Systems evaluation: Determination of criticality, severity, probability of failure and analysis of impact on operational continuity. 2.3. Generation and Management of REM Reports Standardize the technical communication of remote monitoring to ensure that deviations are known, understood, and addressed by the responsible areas. • Automatic reports: Scheduled issuance of reports from REM Data Control (trends, alarms, health KPIs). • REM Condition Report: Severity evaluation based on defined technical criteria (criticality table). • PrePM Report: Report prior to planned maintenance to validate critical conditions of the equipment. • Alerts by condition: Immediate alerts for risks that require urgent attention (high severity).
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