Checklist

Predictive Maintenance Sensor & Data Readiness Audit (Interactive)

An interactive, saveable audit that walks maintenance and reliability teams through sensor coverage, signal quality, data pipelines, labeling, and integration readiness for a practical predictive maintenance pilot.

Interactive Tool

Predictive Maintenance Sensor & Data Readiness Audit

Use this short audit to capture a repeatable view of whether your assets, sensors, and data pipelines are ready for a practical predictive maintenance (PDm) pilot. Answer honestly — the point is to find the highest-impact gaps to fix before starting a model-driven pilot.

List the asset names or IDs included in this pilot, plus location or line if helpful.
An up-to-date inventory mapping sensors to assets and physical locations is essential for planning and troubleshooting.
Estimate 0–100% of the important failure modes or signals that currently have sensors. This helps judge pilot viability.
Choose the descriptor that best fits typical data from the sensors you’ll use.
Enter sampling frequency where applicable, or leave blank if variable.
Missing timestamps, unsynced clocks, or packet loss can make models unreliable.
Edge buffering prevents data loss during network outages and improves training data completeness.
Timestamps should use a common standard (e.g., UTC) and be reliably synchronized for event alignment.
Labeled failure events tied to timestamps are often the most valuable training signal for PDm models.
Is maintenance event data accessible and mapped to asset IDs? This connection is critical for labeling and root-cause checks.
Predictive alerts need an owner and an escalation path before they are useful operationally.
How many days (or months) of raw sensor data are retained? Longer histories help detect degradation patterns.
Use your judgment to score overall readiness considering sensors, data quality, labels, and process readiness.
1.0 10.0
List the highest priority gaps that would prevent a reliable PDm pilot (e.g., no labels, frequent missing data, no CMMS access).
Capture suggested fixes such as sensor wiring checks, timestamp sync, short labeling project, or CMMS mapping so the team can act.
Who completed this audit? Useful for follow-up.
Any other observations, links to sample logs, or references.
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