What data does Industrial IQ need?

Industrial IQ works from CSV exports. Required fields vary by engine, and the docs list minimum viable uploads plus best uploads.

Are ROI results final financial outcomes?

No. ROI pages label benchmark, estimate, assumption, limitation, and customer-specific diagnostic requirements.

Does Industrial IQ write back to ERP?

No. Industrial IQ creates evidence-backed diagnostics, reports, actions, and governance review without ERP write-back.

ReliabilityMind AI Documentation

Engine-to-Value Map

ReliabilityMind AI turns source data into reportable value.

InputWork Order, Description + Material Id, Asset Id, Quantity, Stock On Hand, Priority

DiagnosticWork-order spare availability, false-stockout risk, repeat demand, shutdown readiness, and stale critical work.

OutputMaintenance readiness score, evidence table, confidence tiers, report, actions, and score history.

ValueRepeat failure pattern evidence, planner action queue, maintenance priority quality, and work-order aging risk. Turnaround package readiness scoring and outage-freeze exception list.

Engine operating brief

How this diagnostic works for a decision owner.

Readiness label	Public synthetic demonstration
Business problem	Work-order spare availability, false stockout risk, repeat demand, and shutdown readiness.
Buyer role	Maintenance Director, Reliability Manager, COO, and Plant leaders
Trigger event	Shutdown readiness, false stockout risk, repeat demand, priority work-order backlog, or spare availability questions.
Core source export	Work Order, Description
Optional fields	Material Id, Asset Id, Quantity, Stock On Hand, Priority, Planned Shutdown, Failure Code, Site, Order Date
Upload workflow	Upload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat
Column mapping	Industrial IQ profiles source-fit, suggests field matches, asks the user to normalize unmapped required fields, then recalculates mapping readiness before the engine runs.
Evidence generated	Source-backed evidence rows, reason codes, confidence tiers, review status, assumptions, limitations, and action-owner context.
Score output	Maintenance readiness score
Report output	ReliabilityMind AI Maintenance Readiness Report
Confidence tiers	High-confidence findings can move to review; weak or unsafe matches stay in human-review queues.
Recurring use case	Monthly or quarterly re-uploads create score history, action progress, planning comparison, and renewal value reporting.

Required fields

Minimum viable fields and engine-specific context.

Engine	Required Data File	Required Fields	Optional Fields	Output Generated	Minimum Viable Upload	Engine-Specific Context
ReliabilityMind AI	Work-order export	Work Order, Description	Material Id, Asset Id, Quantity, Stock On Hand, Priority, Planned Shutdown, Failure Code, Site	Maintenance readiness score, evidence, report, actions, score history	Work Order, Description	Material Id, Asset Id, Quantity, Stock On Hand, Priority, Planned Shutdown, Failure Code, Site

Diagnostic logic

What this engine analyzes.

Work-order spare availability, false-stockout risk, repeat demand, shutdown readiness, and stale critical work.
Duplicate-family-aware false-stockout detector using catalog signatures and stock evidence.
Shutdown readiness checklist for planned outage or turnaround rows.

Recurring value

How the engine matures after the first run.

Repeat failure pattern evidence, planner action queue, maintenance priority quality, and work-order aging risk.
Maintenance readiness report by site, priority, failure code, and spare availability.
Reliability manager view that links demand recurrence to corrective action opportunities.
Turnaround package readiness scoring and outage-freeze exception list.
Monthly maintenance readiness trend by site and work-order class.
Service-risk scenario model for critical spare coverage and false-stockout reduction.

Report interpretation

How to read the output.

ReliabilityMind AI Maintenance Readiness Report includes Maintenance readiness score, evidence records, confidence tiers, assumptions, limitations, action tracker items, score history, and no-write-back governance language.

Maintenance Readiness IntelligenceValue lever

Uploaded dataCustomer-specific diagnostic required

ReliabilityMind AIRelated diagnostic engine

EstimateAssumption-labeled until reviewed

Benchmark assumptionUploaded evidenceConfidence tierHuman reviewReportable value

Industrial IQ platform bridge

How this connects to AI2COE Industrial IQ

Maintenance Readiness Intelligence is not treated as an isolated content topic. Industrial IQ connects it to uploaded data, engine evidence, confidence tiers, executive reports, actions, score history, and governance review.

Run Free Industrial IQ Snapshot Explore 8 Diagnostic Engines

PartsCleanse AIcreates catalog evidence and duplicate-family findings.

InventoryMind AIextends catalog signals into inventory risk, dead stock, excess stock, and stockout exposure.

ProcureMind AIconnects supplier and purchase signals to emergency buying, repeat purchases, and leakage.

FinanceMind AItranslates operating findings into working-capital exposure, carrying-cost assumptions, and finance-review scenarios.

AssetMind AIconnects parts to asset relevance, equipment coverage, and plant-register context.

ReliabilityMind AIconnects spare availability to maintenance readiness, false-stockout risk, and shutdown planning.

ReadyMind AIevaluates ERP, data, governance, and AI readiness gaps before transformation spend.

GovernanceMind AImanages confidence, evidence traceability, human review, and auditability.

Documentation context

Use the docs to move from source export to reviewed diagnostic evidence.

Each guide keeps Industrial IQ documentation tied to source preparation, validation, evidence review, and Trust controls.

Docs home

Prepare export Use approved CSV/workbook exports or governed sample data. Map fields Confirm required fields, aliases, source fit, and limitations. Review evidence Inspect findings, confidence tiers, assumptions, and owner actions. Trust controls No ERP write-back, source-file purge after report generation, and human review before action.