About the Unified Manufacturing Data Architecture
Bridging the gap between factory floor reality and enterprise intelligence through a unified data architecture.
Our Mission
To unify production reality with centralized corporate systems in one standards-driven framework that enables teams to unlock AI and advanced analytics without silos, rework, or vendor lock-in.
Why UMDA Was Created
Manufacturers usually take one of two painful routes:
1. Bottom-up Approach
Model production data on the shop floor, then scramble later to bolt on ERP, QMS, and supply-chain context only to find the data doesn’t “fit” together as expected.
2. Top-down Approach
Load enterprise datasets into a data lake, send IoT data to the cloud and discover the disconnect in machine-level detail and the production context AI needs.
Both paths stall when advanced analytics arrive: models can’t find the context they need, teams argue over “who owns the data,” and point-to-point fixes don’t scale.
UMDA was built to merge those two worlds from the foundation:
Edge + Enterprise Together
Production events are enriched in the Edge Intelligence Hub and published in real time to the Unified Namespace, while harmonised tables land in a governed Unified Data Layer.
Standards Over Custom Models
ISA-95/88 models, OPC UA & MQTT protocols, and JSON-Schema data contracts give every domain a common language.
Domain CDMs, Global Harmony
Each Common Data Model is owned locally but designed to plug into others through well-defined Data Products while minimizing turf wars and integration friction.
AI-ready by Design
A Feedback Data Layer captures inferences and outcomes so models improve continuously, not in yearly retrofit projects.
What Makes UMDA Different
Edge-to-Enterprise Context
Enrich data where it’s born, use it where it’s needed.
Real-Time Interoperability
One publish fuels dashboards, historians, and LLM agents simultaneously.
Governed Data Access & Storage
Lineage, quality SLAs, and zero-trust security built in.
Closed-Loop AI
Autonomous agents write results back to operations for measurable improvement.
Where We’re Headed
Open-Source Reference
Open-source reference stacks (Helm, Terraform) for quicker pilots.
Community Extensions
Community CDM extensions across operations, maintenance, labs, supply chain.
AI Governance
Alignment with emerging AI-governance standards (ISO 42001, NIST AI-RMF).
How You Can Use UMDA Today
Benchmark
Your current architecture layer-by-layer to identify gaps and opportunities for improvement.
Pilot
The UNS topic hierarchy on a single line and time your analytics loop for immediate insights.
Learn More
Learn the details of the UMDA, how to deploy it in real manufacturing enterprises, and how it will support future AI technologies in the evolving manufacturing landscape.
Acknowledgements
We’re indebted to ISA, OPC Foundation, GS1, NIST, ISO working groups, MTConnect Institute, Walker Reynolds (the creator of the Unified Namespace), Arlen Nipper and Andy Stanford-Clark (the creators of MQTT), Zhamak Dehghani (the creator of Data Mesh), and the first cohort of manufacturer contributors who proved UMDA on real lines with real deadlines.
Start Your UMDA Journey Today!
Join the growing community of manufacturers who are unifying their data ecosystems with UMDA. Get started today with our implementation guides and resources.