Autonomous Manufacturing

Limitations of Traditional Manufacturing

Existing manufacturing systems rely on hardware-centered fixed production lines, facing the following limitations:

• Lack of flexibility: Significant time and cost required for physical facility reconfiguration when changing products or adjusting production volumes
• Difficulty in pre-validation: Limited methods for validating new production lines or process changes before actual implementation
• Data fragmentation: Equipment, process, and quality data are separated, making integrated analysis and decision-making difficult
• Optimization limitations: Limitations of optimization relying solely on human experience and intuition in complex production environments

The Emergence of Software Defined Factory (SDF)

NVIDIA Omniverse-based digital twin technology enables a new paradigm called Software Defined Factory (SDF). SDF accurately replicates the physical manufacturing environment in the virtual world, enabling the following innovations:

• Virtual-physical environment connection: Creating a digital replica identical to the actual factory, connecting the two worlds in real-time
• Simulation-based decision making: Validating changes in a virtual environment before actual application, reducing risks and costs
• AI-based autonomous manufacturing: Robots and equipment learn and apply optimal work methods through reinforcement learning
• Flexible reconfiguration: Enabling rapid reconfiguration and adaptation of production lines through software control

Core Values of NVIDIA Omniverse-based Digital Twin

Pollux's NVIDIA Omniverse-based digital twin service provides the following core values:

Advanced Design and Simulation

• Precise physical modeling: Minimizing differences between reality and virtual through simulations that accurately reflect actual physical laws
• Pre-validation: Validating new production lines, equipment layouts, and robot deployments in virtual environments before actual construction
• Optimal layout design: Optimizing factory layouts to reduce material movement distances and improve work efficiency

AI-based Autonomous Manufacturing Enhancement

• Application of reinforcement learning: Robots and equipment autonomously learn how to respond to various situations in virtual environments
• Large-scale parallel simulation: Discovering optimal control strategies by simultaneously simulating thousands of scenarios
• Sim-to-Real transfer: Effectively applying models learned in virtual environments to real environments

Operation Optimization and Problem Prevention

• Real-time monitoring: Reflecting actual factory data in the digital twin in real-time to understand operational status
• Predictive maintenance: Early detection of equipment anomalies for preventive maintenance
• Process optimization: Continuously optimizing production flow, resource allocation, and work sequences

Collaboration and Decision Support

• Real-time collaboration: Designers, engineers, and operators collaborate in real-time in the same virtual environment
• Data-driven decision making: Making informed decisions through analysis of various scenarios
• Education and training: Effectively conducting worker training on new equipment and processes in a virtual environment

Concrete Business Outcomes

Manufacturing companies that have adopted NVIDIA Omniverse-based digital twins can achieve the following specific outcomes:

• Reduced design and construction time: Up to 30% reduction in production line design and construction time
• Productivity improvement: 15-25% productivity increase through optimized processes and automation
• Energy efficiency improvement: Up to 20% reduction in energy consumption through optimized equipment operation
• Defect rate reduction: Up to 25% reduction in defect rates through predictive quality management
• Increased flexibility: Up to 50% reduction in production line conversion time when changing products
• Decision-making speed improvement: Up to 40% reduction in decision-making time through simulation-based decision making

Technical Implementation

Pollux's Omniverse-based digital twin solution consists of the following elements:

1. USD Composer: 3D modeling and environment creation for factory buildings, equipment, robots, etc.
2. Isaac Sim: Physics-based simulation of robots and equipment, sensor data simulation
3. Isaac Lab: AI model learning environment for robots and autonomous systems
4. Digital-physical connection technology: Bidirectional data communication between actual equipment and digital twins
5. AI Ops: Verification, management, deployment, and monitoring of trained AI models