Audit

Predictive Maintenance Readiness Checklist

An interactive, structured readiness audit that evaluates sensor coverage, data quality, tagging and failure history, CMMS/workorder integration, spare parts and SLA readiness, team capability, and governance for practical predictive maintenance pilots. The form captures scores, evidence, notes, and candidate assets to prioritize pilots and avoid wasted effort on immature use cases.

Interactive Tool

Predictive Maintenance Readiness Audit

Use this short audit to evaluate whether an asset, system, or site is ready for a practical predictive maintenance pilot. Answer each section candidly, add evidence or notes where useful, and identify an actionable pilot candidate and the top gaps to close before launching. This structured submission will be stored so teams can compare readiness across assets and track improvement over time.

Where the audited asset or equipment is located (e.g., Plant A, Line 3).
Use YYYY-MM-DD or a simple date note.
Tag, asset number, or serial number for the audited machine.
Rate how well the asset has been mapped for criticality and impact (1 = no mapping, 5 = full criticality mapping and business impact documented).
1.0 10.0
Select installed sensor types. Use 'Other' and describe in the evidence field if needed.
Rate how adequate sensors and sample rates are for detecting relevant failure modes (1 = insufficient, 5 = excellent coverage and sampling).
1.0 10.0
Record sample rates, frequency, or examples (e.g., vibration 1kHz, temp every 5 min).
How many days of raw/processed data are kept (approximate).
Is it clear who owns the data and who has access for model building and alerts?
Rate the quality of tags/asset identifiers and the completeness of historical failure and maintenance records (1 = poor, 5 = complete and reliable).
1.0 10.0
Describe how predictive outputs would trigger or integrate with maintenance execution.
Are SLAs defined for responding to condition-based alerts?
Rate readiness of spare parts strategy for predicted failures (1 = no spares, 5 = spare strategy aligns with predicted failures).
1.0 10.0
Rate whether the maintenance team understands condition diagnostics, can execute corrective work, and has training gaps addressed (1 = not ready, 5 = fully capable).
1.0 10.0
List which roles are responsible (e.g., reliability engineer, technician) and any notable training gaps.
A playbook defines steps when an alert occurs (diagnosis, isolation, workorder, parts, escalation).
Rate clarity of governance (who approves pilots, success criteria, budget).
1.0 10.0
1 = Not ready for any pilot, 5 = Ready for a practical pilot with clear ROI and response plan.
1.0 10.0
List the most important obstacles (e.g., missing sensors, poor history, no spare parts).
If you recommend a specific machine or line as a pilot, name it here.
Record links, file names, screenshots, or concrete next actions (note: file upload not supported here).
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