How MES Systems Feed Digital Twins in NVIDIA Omniverse with Production Data

Digital twins are increasingly appearing in modern factory strategies. Process simulations, virtual production lines, scenario testing without the risk of stopping production – this sounds like the future of manufacturing. One of the most recognizable tools in this area is NVIDIA Omniverse.

The problem begins when a digital twin is supposed to stop being a visualization and become a reflection of actual production. For this, data is needed. And this is where MES-class systems play a key role.

What a Digital Twin in NVIDIA Omniverse Is – and What It Isn't

Omniverse is a platform for:

• 3D modeling,
• physics simulation,
• real-time object synchronization,
• testing system behavior in a virtual environment.

It handles questions like:

• what happens if we change the layout,
• how the line will behave with different timing,
• how a new machine will affect material flow.

However, it is not a system for:

• production management,
• recording KPIs,
• understanding shift context, orders, or quality.

Omniverse doesn't know what the factory is currently producing. It can only show this if someone provides it with data.

Why Digital Twins Need Data from MES

A digital twin without operational data is a static model or an advanced demo. To become a decision-making tool, it needs information such as:

• current machine status (production, downtime, failure),
• actual cycle times,
• production orders being executed,
• performance and OEE,
• quality data (scrap, rework),
• shift and operational context.

This is the area where MES operates.

The Role of OmniMES as a Source of Operational Truth

An MES system, such as OmniMES, serves as a logical layer between automation and the visual-analytical layer.

OmniMES:

• collects data from PLCs, SCADA, and IoT,
• normalizes signals from different machines and lines,
• interprets them in the context of the production process,
• calculates KPIs and efficiency indicators,
• provides data in a structured and consistent form.

For a digital twin, this means one thing: access to current, verified production truth, not raw signals.

What MES Integration with Omniverse Looks Like in Practice

Integration scheme:

Machines / PLC
        ↓
   Automation Layer
        ↓
   MES (OmniMES)
        ↓
   API / Data Stream
        ↓
   NVIDIA Omniverse

MES doesn't compete with Omniverse. MES feeds Omniverse.

Omniverse:

• visualizes current states,
• simulates scenarios based on real data,
• enables "what-if" analysis.

MES:

• decides what is true,
• understands the process,
• knows production dependencies.

The Most Common Mistake in Digital Twin Implementations

One of the most common mistakes is attempting to:

• directly connect Omniverse to PLCs,
• bypass the MES layer,
• build a digital twin solely on technical signals.

The result:

• loss of production context,
• lack of data consistency,
• inability to compare plan with execution,
• lack of real business value.

A digital twin without MES doesn't know what it's simulating.

Omniverse and MES – Complementary Systems, Not Alternatives

In a modern factory:

• MES is responsible for operational reality,
• Omniverse for virtual reality.

Only the combination of both layers allows you to:

• test changes without risk,
• analyze production in real-time,
• make decisions based on data, not intuition.

Summary

A digital twin doesn't start with 3D graphics. It starts with data.

An MES system, such as OmniMES, provides:

• structure,
• context,
• information credibility.

NVIDIA Omniverse allows you to:

• see this data,
• understand it,
• simulate the future of production.

Together they create a system. Separately – just tools.

Want to learn more?

• Discover OmniMES capabilities
• Explore NVIDIA Omniverse