Simvis™

Simvis™ is an AI knowledge-driven robot virtual commissioning platform developed by JNE Works. It is an end-to-end solution that automates the entire process from CAD drawing analysis to final robot code generation. It understands design intent from CAD and combines it with accumulated manufacturing knowledge to autonomously generate optimal processes and robot code.

PROBLEMS

Decades of robot manual programming, causing potential loss of hundreds of billions of won per year

Traditional manual robot programming methods cause serious problems and potential losses in manufacturing environments.
In particular, this problem is maximized in the operating environment of cooperative robots, where flexibility and ease of use are key.

  1. High Dependency on Experts

    • High wages & high turnover rates
    • CNC programmer salaries recently exceed KRW 100 million
    • 61% of robotics engineers change jobs within 2 years
    • Shortage of complex robotics specialists
    • Training costs over KRW 3 million per week + ongoing retraining

  2. Severe Shortage of Skilled Workers

    • Few experts possess all required competencies
    • Programming tasks concentrated on specific individuals
    • Projects halt when key experts are absent
    • Extremely high risk for enterprises

  3. Excessive Time & Cost

    • Process change delay losses: Average KRW 5 million+ per minute
    • Process change delays frequently exceed 2-4 weeks
    • High initial & maintenance costs (long-term ROI possible)
    • Post-automation: Productivity +10-15%, Cost -5-7%

WHY SIMVIS?

Simvis™ provides AI- and knowledge-based HRI collaborative robot virtual manufacturing verification

Competitors only provide functions to simulate robot motion and check collisions based on CAD data. Simvis™ has achieved technical differentiation by implementing various AI autonomous functions beyond competitors' 'manual programming' level.
Standalone Robot Simulation
Global Vendors
Rockwell Automation,Visual Components,B&R
Domestic Vendors
Hyundai Robotics, Hanwha Systems, LS ELECTRIC, THiRA-UTECH AMR
Integrated Manufacturing Process Virtual Commissioning
Global Vendors
Siemens,Dassault Systems,NVDIA
Domestic Vendors
Collaborative Robot Virtual Manufacturing & Optimization
Global Vendors
RoboDK
Domestic Vendors
AI & Knowledge-Based Solution JNE Simvis
Simvis™
Core Simulation Model
Omniverse + Isaacsim
OLP/PLC Integration
Very High (ROS2, HIL/SIL)
AI/Simulation Integration
Workflow-based connection integration provided
Vision Language Model (VLM)
CAD/2D drawing interpretation, design intent fusion
Manufacturing Ontology & Knowledge Graph
Native knowledge graph support (semantic reasoning)
Product Type
Cloud-based SaaS

CORE VALUE

Overwhelming ROI Through TCO Reduction

Simvis™ adoption significantly reduces TCO (Total Cost of Ownership), delivering overwhelming ROI proven by real numbers. Additionally, Simvis™ overcomes limitations of traditional manufacturing methods—low flexibility, long lead times, high labor dependency—enabling fundamental manufacturing innovation.
Total Process Time (days)
Reduced from 100 days to 60 days
40% Reduction
Quality Inspection Cycle (hours)
Reduced from 48 hours to 36 hours
25% Reduction
First-Time Quality
75% Improvement
Automated Drilling & Fastening Assembly Time
50% Improvement
Boeing T-7A Trainer Program: Design to First Flight
36 Months Acceleration

CAPABILITIES

Simvis™ consists of an AI pipeline combining LLM, AI Agents, and Knowledge Graph.

  • Robot OLP

    Leveraging NVIDIA Omniverse-based Isaac Sim, we deliver innovation in robot offline programming (OLP). Build digital twins of real environments, simulate collision-free optimal paths to minimize downtime and maximize productivity.

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  • No-Code Robot Auto Programming

    Using NVIDIA Isaac Sim's visual scripting framework, we completely lower the barrier to robot programming. Through an intuitive node-based environment instead of complex text coding, both engineers and non-experts can quickly and accurately design and deploy robot tasks.

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  • Robot Virtual Commissioning

    A core technology that pre-validates and optimizes real robot systems in virtual environments using Isaac Sim. This dramatically saves time and costs while minimizing errors and risks that could occur in real environments.

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  • Automated CAD Analysis

    Converts CAD models into graph structures to automate complex FEA (Finite Element Analysis) and CAE simulation processes. This reduces analysis time from weeks to minutes, enabling performance prediction from early design stages and dramatically reducing development costs and timelines.

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  • 3D Vision Sensor

    Using high-resolution 3D vision sensors, we measure and automatically correct robot end effector position errors in real-time. This enables sub-millimeter precision work exceeding conventional robot repeatability, enabling flexible smart factory implementation.

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DEMO

JNE Works Preparing Market Entry with Proven AI Robot Virtual Commissioning Technology

JNE Works has secured core technologies in AI- and knowledge-based robot virtual commissioning and is preparing market entry with proven domestic solutions validated through numerous PoC (Proof of Concept) implementations.

Major R&D Projects

  1. MSIT AI Global Big Tech Development Program

    Developing "AI-Digital Twin Robot Virtual Commissioning Solution for Aircraft Manufacturing" with Korea Aerospace Industries (KAI) and KENCOA AEROSPACE (2025-2027).

  2. MOTIE Industrial Innovation Technology Development

    Developing "AI-Ontology Based Intelligent Manufacturing Data Orchestra Platform" with Korea Institute of Industrial Technology (KITECH) (2025-2028).

  3. National Demonstration Project Framework

    JNE Works as lead organization has formed a consortium with Korea Aerospace Industries (KAI), Electronics and Telecommunications Research Institute (ETRI), Changwon National University, and Sigong for technology advancement and commercialization. KAI is responsible for virtual commissioning technology demonstration in aircraft manufacturing and on-site solution validation and evaluation.