ReliabilityMind AI | AI2COE Solution

Business problem

Reliability Readiness Diagnostic.

Work-order spare availability, false stockout risk, repeat demand, and shutdown readiness.

The page is not a static brochure. The engine has a working upload, preview, map, validate, analyze, evidence, score, report, action, review, and score-history path inside the Industrial IQ portal.

Buyer ownerMaintenance Director, Reliability Manager, COO, and Plant leaders

Trigger eventERP migration, AI readiness, working-capital pressure, procurement leakage, reliability risk, audit readiness, or recurring operational review.

Input data requiredWork Order, Description

Upload workflowUpload CSV, preview fields, confirm AI-recommended mappings, validate required coverage, normalize where needed, then run the engine.

Diagnostic logicMap source columns, normalize values, run deterministic engine checks, then attach evidence and confidence before report output.

Sample evidence tablePublic sample mode exposes mapped evidence rows before the customer uploads private data.

Score outputMaintenance readiness score: lower values mean higher false-stockout, work-order spare availability, repeat-demand, and shutdown-readiness risk.

Executive report previewSample report pages show the decision narrative, evidence rows, confidence tiers, assumptions, limitations, PDF export, and next actions before private upload.

Report outputReliabilityMind AI Maintenance Readiness Report with HTML, CSV evidence, PDF, and report email status for authenticated runs.

Governance controlsNo ERP write-back, no autonomous supplier outreach, confidence-tier labels, human-review routing, audit metadata, and clear sample-versus-uploaded-data labeling.

Upload workflow

Upload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat.

Step	Layer	Customer experience
1	Upload	CSV export enters the parser. Source file retention rules are disclosed.
2	Map	ERP/CMMS aliases are inferred, then corrected or confirmed by the user.
3	Validate	Required fields, completeness, missing values, and confidence reducers are shown before run.
4	Analyze	Engine-specific analyzers generate findings, evidence, and impact estimates.
5	Govern	Findings receive confidence tiers and human-review status before any action.
6	Report	Executive report, evidence table, action tracker, and score snapshot are produced.

Public proof before account creation

Customers can inspect samples before uploading their own data.

Every sample result is labeled as sample mode. It demonstrates mapping, validation, scoring, evidence, confidence, report structure, action logic, and recurring-review context without claiming customer-specific exposure.

Run Industrial IQ Snapshot Run sample diagnostic Download sample PDF Sample CSV Mapping template Data dictionary Product page

Required data and field dictionary

Accepted fields, aliases, and mapping expectations.

Input	Need	Common aliases	Meaning
Work Order	Yes	work_order; wo; work_order_id; aufnr; order; maintenance_order; wo_number; maintenance_order_number	Work order, maintenance order, job plan, notification, or shutdown package identifier.
Description	Yes	description; item_description; material_description; maktx; short_text; part_description; long_text; desc	Item, part, asset, work-order, finding, or source-record description used by the engine.
Material Id	Recommended	material; material_id; material_number; matnr; item; item_number; item_id; sku; part; part_number; stock_code	Unique material, SKU, item, or spare-part identifier from the source system.
Asset Id	Recommended	asset_id; equipment; equipment_id; asset; tag; functional_location; floc; equipment_tag; asset_tag	Equipment, asset, functional location, tag, or plant-register identifier.
Quantity	Recommended	quantity; qty; stock_qty; on_hand; qty_on_hand; unrestricted; labst; stock_on_hand	Quantity, balance, order quantity, stock quantity, or demand quantity depending on engine.
Stock On Hand	Recommended	stock_on_hand; on_hand; qty_on_hand; unrestricted; available_stock; stock_qty; labst	Current available stock balance or on-hand inventory quantity.
Priority	Recommended	priority; wo_priority; criticality; maintenance_priority; work_order_priority; work_priority; wo_priority_code	Work-order, maintenance, procurement, or operational priority.
Planned Shutdown	Recommended	planned_shutdown; shutdown; turnaround; outage; ta_flag; shutdown_flag; outage_flag; turnaround_flag	Shutdown, turnaround, outage, campaign, or maintenance-window flag.
Failure Code	Recommended	failure_code; problem_code; cause_code; failure_mode; damage_code	Failure code, problem code, cause code, repair code, or maintenance reason.
Site	Recommended	site; plant; werks; location; storeroom; warehouse; depot; facility	Plant, site, warehouse, storeroom, region, location, or operating unit.
Order Date	Recommended	order_date; po_date; created_date; document_date; posting_date	Purchase order, requisition, work order, or transaction date.

Recommended diagnostic data pack

What to upload for a stronger run.

Recommended file	Fields that improve confidence
Work-order export	work order, asset, part, priority, planned shutdown, failure code
Inventory export	stock on hand, site, material ID, quantity
Asset register	asset criticality, equipment class, plant context

Business impact model

Why this matters to the buyer committee.

Maintenance readiness

Maintenance readiness model

Work-order part availability, repeat demand, false-stockout risk, shutdown readiness.

Uptime control

Uptime control model

Risk signals tied to planned work, critical spares, and recurring maintenance demand.

Decision output

Decision output model

Readiness score, work-order evidence, shutdown checklist, reliability report.

Evidence and confidence

What the report proves.

Output layer	Example	Why it matters
Score	Maintenance readiness score	0-100 signal with risk level and trend-ready snapshot.
Score formula	Deterministic calculation	The report exposes the scoring formula and component inputs; random scores are not used.
Finding	ReliabilityMind AI Maintenance Readiness Report	Issue title, severity, source engine, and owner-facing action.
Evidence	Mapped source records	Source-row references, relevant fields, analyzer reason codes, and confidence tier.
Evidence graph	Source -> finding -> evidence -> action	The result carries an evidence graph for review, report, action, and score-history continuity.
Confidence	High / Medium / Needs Review	Coverage, completeness, source-field quality, and analyzer agreement.
Action	Owner review item	Recommended action, priority, due window, and review status.
Renewal value	Recurring management view	The report shows exposure identified, review queue size, actions created, and next review cadence.

Buyer interpretation

One diagnostic, multiple executive decisions.

Buyer	Decision question	Evidence source
CFO	Can the finding be tied to capital exposure, carrying cost, leakage, or payback discipline?	ReliabilityMind AI
COO	Does the evidence reduce operating risk, downtime exposure, site friction, or service disruption?	ReliabilityMind AI
CIO / ERP owner	Are source fields mapped, export quality visible, and ERP write-back avoided unless governed?	ReliabilityMind AI
Procurement	Does the diagnostic expose supplier, PO, duplicate spend, stocked-but-purchased, or price-variance risk?	ReliabilityMind AI
Maintenance / Reliability	Does the evidence affect work-order readiness, false stockout, shutdown coverage, or critical-spare confidence?	ReliabilityMind AI
Data governance	Can findings be reviewed, accepted, rejected, audited, and defended after the report is shared?	ReliabilityMind AI

Trust controls

This engine is governed before operational action.

Trust control

No ERP write-back

Findings are recommendations and review items, not autonomous ERP changes.

Trust control

Evidence traceability

Every finding links back to source records, mapped fields, and reason codes.

Trust control

Confidence tiers

High, medium, low, and needs-review logic is visible before action.

Trust control

False-positive control

Unsafe lookalikes are separated from high-confidence findings.

Trust control

Human review

Owners can accept, reject, defer, assign, or request more data.

Trust control

Audit trail

Report exports, reviewer actions, and status changes remain traceable.

FAQ

Questions buyers ask before running ReliabilityMind AI.

What data does ReliabilityMind AI need?

ReliabilityMind AI requires Work Order, Description. Optional fields such as Material Id, Asset Id, Quantity, Stock On Hand, Priority, Planned Shutdown improve confidence and business-impact precision.

What does ReliabilityMind AI produce?

It produces ReliabilityMind AI Maintenance Readiness Report, a 0-100 maintenance readiness score, evidence records, confidence tiers, recommended actions, and a review-ready executive summary.

Does AI2COE write back to SAP, Maximo, Oracle, or any CMMS?

No. AI2COE diagnostics are decision-support outputs. They do not change ERP, EAM, CMMS, procurement, inventory, or asset records automatically.

How does confidence tiering work?

Findings are ranked by source-field coverage, data completeness, evidence quality, analyzer agreement, and whether a human owner should review the recommendation before action.

How should leadership use the report?

Use the report to decide whether the issue is measurable, material, governable, and worth funding before starting a larger ERP, inventory, procurement, maintenance, or AI transformation program.