CT Scan Machine Failure Prediction and Alert System
This system predicts potential CT scan machine failures using sensor data and machine learning. It provides real-time insights through Grafana dashboards and triggers alerts via Prometheus when failure risks exceed set thresholds.
Click here to view the demo: medicomachineries.tech4bizsolutions.com
Implementation Highlights
- Load the CSV file containing sensor data and the pre-trained machine learning model using libraries like pandas and joblib.
- Preprocess the data and pass it to the model to generate failure predictions.
- Implement a Prometheus metrics exporter to expose prediction results and model statistics as metrics.
- Set up a Grafana dashboard to visualize failure predictions, probabilities, and trends for real-time monitoring.
- Configure Prometheus alert rules to monitor metrics like failure probability exceeding a threshold or abnormal patterns.
- Integrate alert notifications with communication tools such as email, Slack, or SMS using Prometheus Alertmanager.
Outcome
Early detection of potential failures, leading to reduced unplanned downtime and improved maintenance scheduling.
Enhanced machine longevity and operational efficiency by proactively addressing issues before they cause major failures.