Packaging process validation
Review package movement, spacing, placement, equipment interaction, and operator steps before physical trials or automation changes.
← Solutions
Process Simulation and Virtual Planning
Make physical process decisions in a virtual environment
Use FactVerse Designer to compare layouts, model operating flows, run virtual trials, and connect selected scenarios to physics and robotics simulation before changes reach the floor.
Key Capabilities
Connect data, workflows, and field execution so teams can understand context, act faster, and keep work traceable.
- Layout and flow planning
Build production cells, packaging lines, warehouse zones, material paths, work areas, and operating constraints in FactVerse Designer.
- Scenario authoring and comparison
Represent people, equipment, materials, stations, timing, and work steps, then compare alternatives in the same spatial and operational context.
- Data-informed virtual trials
Bring selected live, historical, or engineering data into the scenario when teams need to compare assumptions with actual operating conditions.
- Physics-based validation
Extend motion, collision, placement, contact, and material-interaction scenarios through OpenUSD and NVIDIA simulation technologies at the fidelity required for the decision.
- Robotics and Physical AI preparation
Reuse structured scenes and SimReady assets in Isaac Sim, Isaac Lab, or Newton-oriented workflows for robot testing, learning, and sim-to-real preparation where the project requires it.
- Reusable execution context
Carry approved scenes, assumptions, sequences, and visual evidence into engineering review, training, implementation, and later optimization.
Use Cases
Practical applications and proven success scenarios across industries.
Production layout planning
Compare lines, workstations, buffers, access areas, and material flow before committing to changes in the real facility.
Warehouse and intralogistics planning
Evaluate zones, routes, picking flows, staging areas, vehicle movement, and resource allocation for a proposed operating scenario.
Virtual trials and commissioning preparation
Rehearse process sequences, equipment interactions, and operating procedures so teams arrive on site with aligned assumptions and a clear test plan.
Robotics scene and task preparation
Prepare reusable factory context and task scenarios for robot testing, synthetic data, policy learning, and sim-to-real validation workflows.
Make the decision before the physical change
Layout reviews, spreadsheets, and static models can explain where equipment will sit, but they rarely show how people, machines, materials, timing, and space will interact during operation. Teams often discover waiting points, access conflicts, awkward handoffs, or physical behavior only after equipment, tooling, or site work is already committed.
Process Simulation and Virtual Planning uses FactVerse Designer to turn those assumptions into a reviewable operating scenario. Teams can compare alternatives, run virtual trials, and decide which questions need deeper physics, engineering, or robotics validation before work reaches the floor.
From source data to a virtual trial
- Define the decision - Identify the layout, flow, interaction, capacity, or robotics question and the evidence needed to answer it.
- Prepare the scene - Build the facility, equipment, work areas, paths, materials, and constraints in FactVerse Designer.
- Model the process - Add actors, states, timing, sequences, handoffs, and scenario variables.
- Connect relevant data - Use Data Fusion Services when historical, live, or engineering data should inform assumptions or comparisons.
- Run and compare - Review alternatives for flow, waiting, access, collision, placement, resource use, and operational feasibility.
- Increase fidelity where needed - Extend selected questions into OpenUSD, Omniverse, Isaac, PhysX, or Newton workflows according to the task.
- Prepare execution - Carry the approved scene, assumptions, evidence, and test plan into engineering, implementation, training, or robotics work.
How the technology layers fit together
FactVerse Designer is the authoring and planning environment. It creates the spatial scene, process logic, scenario variants, and reusable operating context. OpenUSD provides a composable foundation for exchanging structured scenes and SimReady assets. NVIDIA Omniverse is now delivered as accelerated libraries, microservices, SDKs, and APIs that can add rendering, physics, storage, and integration capabilities to industrial and Physical AI applications.
For robotics, Isaac Sim and Isaac Lab extend the workflow into robot simulation, synthetic data, and learning. PhysX supports physical behavior such as motion, collision, and contact. Newton provides an extensible, GPU-accelerated physics foundation for robot learning and development. A project uses only the layers required by its decision and validation plan.
Planning, physics, and engineering evidence
Different questions need different levels of fidelity. Early layout and workflow decisions may be answered by geometry, paths, timing, and discrete behavior. Motion, collision, contact, or placement questions need physics-based behavior. Safety-critical, structural, thermal, fluid, or regulated decisions may require engineering analysis, measured data, specialist tools, and physical testing in addition to the digital twin.
The project defines the acceptance envelope first, then selects the scene detail, solver, calibration data, and comparison method that can produce useful evidence for that decision.
Where teams apply the workflow
- Packaging cells and material interaction
- Production-line and workstation layout
- Warehouse zoning, picking, staging, and vehicle movement
- Virtual trials before installation or commissioning
- Operator sequence review and training preparation
- Robotics scene generation, synthetic data, and sim-to-real preparation
Reuse the scene beyond one review
A validated scene can continue into design review, stakeholder communication, work instructions, operator training, automation planning, and robotics development. Reuse matters because each later team can work from the same facility context, asset identity, assumptions, and approved scenario instead of rebuilding the environment from scratch.
Public evidence
DataMesh has publicly demonstrated production-line planning with Chen Hsong, intralogistics automation validation with Gyro, and simulation digital twin workflows with NVIDIA Omniverse. Each customer scenario establishes its own required fidelity, acceptance method, and expected outcome.
Start with one decision and one representative scenario
A useful pilot should focus on a real upcoming change, representative assets, agreed assumptions, and an explicit acceptance method. DataMesh and the customer can then confirm the scene pipeline, scenario logic, data inputs, simulation depth, comparison evidence, and handoff before expanding to a larger line, facility, or robotics program.
Frequently Asked Questions
FactVerse Designer owns scene composition, layout planning, process logic, behavior, and scenario authoring. Other DataMesh and NVIDIA technologies extend that authored context when data connection, rendering, physics, or robotics workflows are required.
OpenUSD provides a composable scene and asset foundation. NVIDIA Omniverse libraries and services can add accelerated rendering, physics, storage, and application integration to selected workflows without changing Designer's role as the planning and authoring environment.
PhysX supports physical behavior such as rigid-body motion and contact. Isaac Sim and Isaac Lab support robotics simulation and learning workflows. Newton can support extensible, GPU-accelerated robot physics. The project selects the simulation stack according to the task and required validation evidence.
Fidelity depends on the geometry, material assumptions, solver, calibration data, and decision being tested. Teams define an acceptance envelope and compare important results with engineering calculations, measured data, or physical trials when the decision requires it.
A focused pilot typically delivers a representative scene, defined scenarios, assumptions, comparison results, visual evidence, and a plan for connecting the approved workflow to engineering, training, automation, or robotics work.
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