Plant Reliability Assessment

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Do not enter facility names, site locations, or vendor-specific details. Responses are aggregated for assessment themes only.

Profile Anonymous facility profile — non-confidential

Industry sector *

Respondent role *

Section A Asset registry & criticality classification

Q1. Is your critical equipment inventory fully registered in your CMMS (Computerized Maintenance Management System) / ERP (Enterprise Resource Planning) system? *

Yes — complete and currentIn progressPartially — major equipment onlyNo formal registry exists

Q2. What percentage of total equipment is formally classified as critical? *

Less than 10%10 – 20%More than 20%No formal criticality ranking done

Q3. What methodology is used for criticality ranking? *Select all that apply

Risk Matrix (Consequence × Likelihood)Engineering judgement onlyRCM (Reliability-Centred Maintenance) based criticality analysisNone / ad hocRAM (Reliability, Availability & Maintainability) modellingOther

Section B Maintenance strategy & work management

Q4. What maintenance strategies are actively used at your facility? *Select all that apply

Time-Based Preventive (PM)RCM (Reliability-Centred Maintenance)Condition-Based (CBM / PdM)Prescriptive / AI-driven recommendationsRun-to-Failure (RTF) for non-criticalNo formal strategy — reactive only

Q5. Do you formally review and optimize PM (Preventive Maintenance) task lists after turnarounds or major inspections? *

Yes — structured PM optimization processRarely / neverOccasionally — informal reviewPlanning to implement

Q6. What is the approximate split of your annual maintenance spend? * Enter percentages that total 100%. Typical world-class target: Scheduled ≥ 70%, Unscheduled ≤ 20%, Emergency < 10%.

Scheduled % Unscheduled % Emergency / Reactive %

Section C Condition monitoring & equipment health

Q7. Which condition monitoring / PdM (Predictive Maintenance) technologies are deployed? *Select all that apply

Vibration analysis (online or periodic)Motor current signature analysisThermography / infrared scanningProcess-parameter trending (historian-based)Ultrasonic leak / thickness testingOil & lube analysis (LIMS-tracked)None currently deployed

Q8. Is your equipment health monitoring system integrated with the control system or historian? *

Yes — fully integrated (real-time data feed)Stand-alone, no integrationPartial — manual data transferNo health monitoring system in place

Q9. Additional notes on health monitoring (optional) Generic comments only — no site names, vendor names, or proprietary details.

Section D Failure analysis & knowledge capture

Q10. Have FMEA / FMECA (Failure Mode & Effects Analysis) been completed for critical assets? *

Yes — all critical assets coveredIn progressYes — partially (select equipment)No — not yet started

Q11. What asset information is captured and maintained in your CMMS / ERP? *Select all that apply

Spare parts availability & min/max stockRoot cause findings (RCFA)Maintenance history & observationsEquipment performance / OEE (Overall Equipment Effectiveness) dataKnown failure modesNone of the above

Q12. Do you have a formal workflow to capture RCFA (Root Cause Failure Analysis) for bad actors? *

Yes — structured RCFA (Root Cause Failure Analysis) database with trackingRCFA done verbally, not documentedYes — but informal / spreadsheet-basedNo formal RCFA process

Q13. How is operator field knowledge (observations, near-misses, anomalies) captured? *Select all that apply

Structured digital rounds on mobile/tabletIntegrated with CMMS (Computerized Maintenance Management System) as notificationsPaper-based rounds — manually entered laterVoice-to-text / AI-assisted captureVerbal handover only — not recordedNot systematically captured

Section E Reliability modelling & performance metrics

Q14. Do you have a RAM (Reliability, Availability & Maintainability) model for your facility or key units? *

Yes — dynamic model, regularly updatedPartial — for specific units onlyYes — static model (last updated > 2 years ago)No RAM (Reliability, Availability & Maintainability) model in place

Q15. Which KPIs (Key Performance Indicators) are formally tracked for reliability performance? *Select all that apply

OEE (Overall Equipment Effectiveness)Schedule ComplianceMTBF (Mean Time Between Failures)Maintenance Cost as % of RAV (Replacement Asset Value)MTTR (Mean Time to Repair)PMC % (Planned Maintenance Compliance)None tracked formally

Q16. How would you rate the accuracy and completeness of your equipment failure data for trend analysis? *

1 — Very poor2 — Poor3 — Moderate4 — Good5 — Excellent

Section F Digital systems & data infrastructure

Q17. Which primary digital systems are used for reliability and maintenance activities? *Select all that apply

SAP PM (Plant Maintenance)IBM MaximoInfor EAMOracle eAMOSIsoft PI (process historian)AspenTechMicrosoft Excel / spreadsheetsCustom in-house toolsOther

Q17a. If “Other” system (optional)

Q18. How well are your process historian data and maintenance records linked or correlated? *

Tightly integrated — automatic correlationSiloed — no linkage between systemsLoosely linked — manual matching requiredNo process historian in place

Q19. Are electronic devices (tablets, smartphones, wearables) used during operator / technician field rounds? *

Yes — fully deployedPlanned for next 12 monthsPilot in progressNo — paper-based only

Q20. Are laboratory samples (lube oil, corrosion coupons, process fluid) tracked in a LIMS (Laboratory Information Management System) or equivalent? *

Yes — LIMS (Laboratory Information Management System) with automated alertsTracked in spreadsheets onlyYes — LIMS but manual follow-upNot systematically tracked

Section G AI (Artificial Intelligence) & advanced analytics readiness

Q21. Does your facility have sufficient clean, timestamped historian data to support predictive analytics? *

Yes — data is clean, labelled, and accessible via APIPartial — limited tags / poor data qualityYes — but data quality and access need improvementNo — data not available or inaccessible

Q22. What is your organization's current stance on AI-assisted reliability tools? *

Actively piloting or deploying AI toolsSkeptical — need to see demonstrated ROI firstExploring — evaluating vendors / use casesNot a current priorityOpen in principle — budget / expertise constraints

Q23. Which AI / advanced analytics use cases are of highest interest? *Select all that apply

Anomaly detection & early warning alertsMaintenance schedule optimizationRUL (Remaining Useful Life) predictionProcess-reliability correlation (historian mining)Automated RCFA using AI pattern matchingOperator knowledge capture (voice-to-logic)Not sure — need guidance

Q24. How would you rate your team's capability to interpret and act on AI-generated reliability insights? *

1 — No capability2 — Limited3 — Moderate4 — Proficient5 — Advanced

Section H Top reliability challenges & comments

Q25. What are the top 2–3 reliability challenges your facility faces? What outcomes matter most? (optional) Free text — no facility names, locations, or confidential details please.