Sensor Reliability Checklist

LinkedIn Post 11: Sensor Reliability Checklist

Quick test: Can you answer these questions about the sensors in your AI-powered predictive maintenance system?

□ What is the accuracy specification for each sensor?

□ When was each sensor last calibrated?

□ How do you detect sensor drift between calibrations?

□ Which sensors have failed a recent calibration check?

□ Which AI-driven inspection recommendations were made using data from non-certified sensors?

□ Do you have a documented procedure for removing unreliable sensors from service?

If you can't confidently answer these questions, your organization has a sensor governance gap.

Sensors are the foundation of AI. Unreliable sensors = unreliable AI decisions.

APMGA-SENSOR addresses this systematically:

1. Identify all sensors in the system

2. Define reliability standards for safety-critical measurements

3. Validate sensors before deployment

4. Monitor for drift during operation

5. Recalibrate regularly and document results

6. Remove unreliable sensors from service

7. Maintain a sensor registry

This isn't bureaucracy. It's the difference between trustworthy AI and AI running on borrowed time.

Start with the checklist above. Be honest about where you are. Then build from there.