Predictive Maintenance Readiness Audit (PdM readiness scorecard)

{"Title":"Predictive Maintenance Readiness Audit (PdM readiness scorecard)","IntroductionHtml":"

This short audit helps you quickly assess whether your site is ready to run a practical predictive maintenance (PdM) pilot without wasting budget on immature use cases. Complete the five section scores (0-5) and optionally add notes. The total score (maximum 25) indicates a recommended next step.

Scoring scale (0–5)

• 0 — No capability or far from acceptable
• 1–2 — Significant gaps; many blockers
• 3 — Basic capability present but unstable or inconsistent
• 4 — Good capability with a few gaps
• 5 — Strong, reliable capability suitable for pilots

How to use

Answer each section with the best current site-level assessment for the asset class you plan to pilot (rotating equipment, pumps, motors, compressors, etc.). Be pragmatic: a pilot typically needs a solid 16+ overall score and minimal gaps in sensor coverage and data quality.

Band guidance (total score out of 25)

• 0–8: Not ready — Major blockers. Focus on basic sensing, data capture, and maintenance process hygiene before attempting PdM.
• 9–15: Partially ready — Some foundations exist but remedial work needed (data gaps, CMMS linkage, clear decision rules).
• 16–20: Mostly ready — Good candidate for a scoped pilot if you address a couple of prioritized gaps.
• 21–25: Ready — Strong readiness. Proceed with a well-scoped pilot focused on clear business outcomes.

","SubmitLabel":"Save audit","SuccessMessage":"Thanks — your responses are saved. To get an immediate interpretation: add the five section scores and compare to the band guidance. Recommended next actions are shown below based on the band you fall into.\n\nIf your total is 0–8: Stop and fix fundamentals — install key sensors for critical failure modes, ensure reliable data capture and timestamps, and establish basic work-order workflows.\nIf your total is 9–15: Prioritize highest-impact gaps — fix the worst sensor or data quality issues, map failure modes to sensors, and pilot CMMS integration for automatic work orders.\nIf your total is 16–20: Address remaining gaps (spares, decision thresholds, training) and run a tightly scoped pilot on a small asset set with clear KPIs.\nIf your total is 21–25: Design a pilot to validate predictions end-to-end (detection -> disposition -> work order -> measure MTTR/MTBF improvements). Capture lessons and scale." ,"DataType":"PdMReadinessAudit","SchemaVersion":"1.0","Fields":[{"Key":"sensor_coverage","Type":"scale","Label":"Sensor coverage (0-5)","HelpText":"Are sensors installed at the right points and in sufficient quantity to capture common failure modes? Consider sampling rate, placement, and whether critical assets lack instrumentation.","Required":true,"Min":0,"Max":5},{"Key":"sensor_coverage_comments","Type":"textarea","Label":"Notes on sensor coverage","HelpText":"List which asset types have sensors, which failure modes are uncovered, known blind spots, and tagging/asset-identification issues."},{"Key":"data_quality","Type":"scale","Label":"Data quality & retention (0-5)","HelpText":"Is sensor data reliable, time-synced, labeled, and retained long enough for modeling? Consider gaps, noise, missing timestamps, and accessibility for analytics.","Required":true,"Min":0,"Max":5},{"Key":"data_quality_comments","Type":"textarea","Label":"Notes on data quality & retention","HelpText":"Mention retention policies, known gaps, missing metadata, and whether you can export data for offline analysis."},{"Key":"cmms_integration","Type":"scale","Label":"CMMS & work order integration (0-5)","HelpText":"Can PdM alerts be mapped to assets and automatically create or trigger work orders? Are asset IDs, failure codes, and spares lists consistent?","Required":true,"Min":0,"Max":5},{"Key":"cmms_comments","Type":"textarea","Label":"Notes on CMMS & work order integration","HelpText":"Note missing links, manual handoffs, lack of auto-WO, or inconsistent asset master data."},{"Key":"processes","Type":"scale","Label":"Maintenance processes & decision rules (0-5)","HelpText":"Are there clear escalation paths and documented decision rules (when to inspect, when to act)? Are acceptance criteria and permitted downtime windows defined?","Required":true,"Min":0,"Max":5},{"Key":"processes_comments","Type":"textarea","Label":"Notes on processes & decision rules","HelpText":"Capture existing SOPs, thresholds, risk tolerances, spares availability, and any regulatory constraints."},{"Key":"skills_change_mgmt","Type":"scale","Label":"Skills and change management (0-5)","HelpText":"Do maintenance and operations teams understand PdM outputs? Is leadership committed to acting on predictions, and are training and roles defined?","Required":true,"Min":0,"Max":5},{"Key":"skills_comments","Type":"textarea","Label":"Notes on skills & change management","HelpText":"Identify training needs, vendor dependence, presence of local champions, and communication across shifts."},{"Key":"total_score","Type":"number","Label":"Total score (0–25)","HelpText":"Add the five section scores and enter the total here. This helps tracking over time. (Max 25)","Required":false,"Min":0,"Max":25},{"Key":"overall_observations","Type":"textarea","Label":"Overall observations & priority recommendations","HelpText":"Summarize the highest-impact gaps and the top 3 remedial actions you would take before or during a pilot."}]}