Manufacturing Excellence Journey
Line 3 went down twice this week. The cause is buried in different systems.
The Challenge
Manufacturing operations struggle with:
- Scattered data - SCADA, MES, historians, quality systems
- No unified view - OEE calculated differently everywhere
- Reactive troubleshooting - Problems found after damage is done
- Manual reporting - Shift reports, quality metrics, production summaries
Traditional approaches fail because:
- Data lives in system silos
- Query logic isn't standardized or documented
- AI insights can't be traced to source data
- Different teams calculate metrics differently
The Solution: Governed Production Intelligence
OpenIndustrial provides the Control Plane for your production data:
| Capability | How It Helps |
|---|---|
| Unified production view | All systems, one governed layer |
| Standardized metrics | OEE, quality, downtime—defined once, trusted everywhere |
| Full audit trail | Every query, every metric, every report—tracked |
| MCP-native AI | Claude or Copilot analyzing governed production data |
When the plant manager asks "Why did we miss target?", you'll show them the exact query—and every data point that fed it.
What You'll Build
By the end of this journey:
| Component | Description |
|---|---|
| Connections | SCADA, MES, historian, quality systems |
| Surfaces | Plant, line, cell, station hierarchy |
| Warm queries | OEE, cycle time, quality, downtime analysis |
| API endpoints | Dashboard, MES, alerting integration |
| MCP integration | AI-powered production analysis |
Two Tracks
Track A: Hybrid Integration
"Govern Without Disrupting Production"
You have SCADA, MES, and historians running. This track adds governance:
- Connect existing production data via IoT Hub
- Create surfaces that organize by line, cell, station
- Build standardized OEE and quality queries with Azi
- Integrate with existing dashboards
Track B: Full System
"Author Your Production Intelligence"
Starting fresh or want complete control:
- Design your production data architecture
- Create a complete surface hierarchy
- Build a comprehensive query library
- Establish team permissions for operations, quality, maintenance
Prerequisites
| Requirement | Details |
|---|---|
| OpenIndustrial account | Free tier works for this journey |
| Azure subscription | For IoT Hub connections |
| Data sources | SCADA, MES, historian, or simulator |
| Time | ~2 hours for Hybrid, ~4 hours for Full |
No SCADA connection yet? Use our production simulator to follow along. The patterns work identically.
Why Governed Production Data Matters
OEE That Everyone Trusts
| Problem | Governed Solution |
|---|---|
| "My OEE is different from yours" | One query, one definition, auditable |
| "Where does this number come from?" | Full data lineage to source |
| "Can we trust the dashboard?" | Governed query = documented logic |
Quality Traceability
- Lot tracking: Which batches, which inputs, which outputs
- Deviation analysis: What changed when quality dropped
- Root cause: Data-driven, not gut-driven
Category Metrics
At the end of this journey:
| Metric | Target |
|---|---|
| Time to First Governed Query | < 30 minutes |
| Production queries built | 5+ |
| Audit coverage | 100% of production insights |
| AI integration | At least 1 MCP-native AI |
Choose Your Track
Hybrid Integration
Add governance to existing SCADA, MES, and historians. No rip-and-replace.
Full System
Build from scratch. Complete control over production data architecture.
What's Next
| Track | Link |
|---|---|
| Start with Hybrid | Hybrid Track → |
| Start with Full | Full Track → |
| See common patterns | Patterns → |
On this page
- FrontmatterVersion: 1 DocumentType: Guide Title: "Manufacturing" Summary: "Pull SCADA, MES, and historian data together so OEE means one thing and downtime traces to a cause. Choose the hybrid or the full track." Created: 2026-01-19
- Manufacturing Excellence Journey