PREDICTIVE MAINTENANCE MONITORING PROCESS

Created by ChecklistGuro (https://checklistguro.com)

[ ] Fetch Sensor Telemetry Data: Retrieve the latest temperature, vibration, and pressure readings from the IoT sensor data model.
[ ] Fetch Equipment Metadata: Retrieve machine specifications, installation date, and threshold limits from the Equipment data model.
[ ] Calculate Health Score: Execute a formula to calculate a degradation score based on current sensor values vs. historical thresholds.
[ ] Update Equipment Status: Update the 'Current Condition' field in the Equipment data model based on the calculated health score.
[ ] Calculate Average Vibration Trend: Calculate the average vibration levels over the last 7 days to identify upward trends.
[ ] Determine Anomaly Threshold: Compare the current calculated health score against the predefined critical limit.
[ ] Assign Inspection Task: Create a task for the Maintenance Technician to perform a physical inspection of the flagged machine.
[ ] Create Maintenance Alert Entry: Create a new entry in the 'Alerts' data model documenting the anomaly detection.
[ ] Notify Maintenance Manager: Send an email alert to the Manager containing the machine ID and the detected anomaly details.
[ ] Create Work Order: Create a high-priority task in the Work Order data model for the repair crew.
[ ] Log Inspection Findings: Update the 'Last Inspection Result' field in the Equipment model once the technician completes the task.
[ ] Create Maintenance Log: Create a permanent record entry in the Maintenance History model for audit purposes.
[ ] Generate Weekly Health Report: Generate a summary report of all equipment health scores and completed maintenance tasks for the week.
[ ] Urgent Critical Alert SMS: Send an urgent SMS to the On-Call Engineer if the health score drops below the critical threshold.
[ ] Cleanup Temporary Telemetry: Delete temporary high-frequency sensor cache entries once they have been aggregated into the daily trend.

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