Wistron Advances Energy Efficiency in Manufacturing with AI and NVIDIA Omniverse

Summary

Wistron, a global leader in information and communications products, has made significant strides in enhancing energy efficiency in manufacturing through the use of AI and NVIDIA Omniverse. By developing a digital twin platform and AI-enabled simulation tools, Wistron has been able to optimize the design, performance, and energy efficiency of their run-in test rooms, potentially saving up to 10% in energy consumption.

Revolutionizing Energy Efficiency in Manufacturing

In the quest to reduce energy consumption and environmental impact, companies are turning to advanced technologies like AI and digital twins. Wistron, a leading global supplier of information and communications products, has taken a significant step forward in this direction by leveraging AI and NVIDIA Omniverse to enhance energy efficiency in manufacturing.

Building Digital Twins of Test Rooms

Wistron’s developers built a digital twin platform and AI-enabled simulation tools to optimize the design, performance, and energy efficiency of their run-in test rooms in new NVIDIA DGX and NVIDIA HGX factories. This was achieved by using NVIDIA Omniverse, a platform for industrial digitization, and Universal Scene Description (OpenUSD) to connect the digital twin platform to their building management system and IoT hub.

Enhancing Operational Efficiency with OpenUSD and AI

The integration of OpenUSD enabled real-time collaboration for remote teams, streamlining the review of facility layouts and accelerating decision-making in facility planning and operations. Wistron developers also built and integrated physics-informed AI models into the digital twin platform using the open-source NVIDIA Modulus framework. These AI models help accelerate simulation work, improve thermal dynamics, and reduce operational risks, ensuring that cooling systems perform optimally even under demanding conditions.

Accelerating Simulation and Predicting Risk with Physics-Informed AI

The use of physics-informed AI models allows Wistron to approximate the underlying physics of their thermal systems, providing fast and accurate predictions of temperature distributions and thermal behaviors within their run-in test rooms. Teams can now identify facility hotspots and forecast core temperatures up to 30 minutes in advance.

Real-Time Collaboration and Enhanced Decision-Making

The digital twin platform, powered by NVIDIA Omniverse and OpenUSD, enables real-time data from thousands of physical sensors across their facilities. This includes core temperature, inlet temperature of supercomputing facilities, and the return temperature of air conditioning systems. This real-time data facilitates collaboration and decision-making, allowing teams to make informed decisions quickly.

The Impact of AI and Digital Twins on Energy Efficiency

The use of AI and digital twins has the potential to significantly reduce energy consumption. Wistron’s digital twin platform and AI-enabled simulation tools can save up to 10% in energy consumption. This is a significant step forward in reducing environmental impact and operational costs.

The Future of Energy Efficiency in Manufacturing

As companies continue to explore ways to reduce energy consumption and environmental impact, the use of AI and digital twins will play a crucial role. Wistron’s success in enhancing energy efficiency in manufacturing through AI and NVIDIA Omniverse sets a precedent for other companies to follow.

Key Takeaways

• Digital Twins: Wistron built a digital twin platform and AI-enabled simulation tools to optimize the design, performance, and energy efficiency of their run-in test rooms.
• OpenUSD and AI: The integration of OpenUSD enabled real-time collaboration for remote teams, streamlining the review of facility layouts and accelerating decision-making in facility planning and operations.
• Physics-Informed AI: Physics-informed AI models help accelerate simulation work, improve thermal dynamics, and reduce operational risks, ensuring that cooling systems perform optimally even under demanding conditions.
• Real-Time Collaboration: The digital twin platform, powered by NVIDIA Omniverse and OpenUSD, enables real-time data from thousands of physical sensors across their facilities, facilitating collaboration and decision-making.
• Energy Efficiency: The use of AI and digital twins has the potential to significantly reduce energy consumption, with Wistron’s digital twin platform and AI-enabled simulation tools saving up to 10% in energy consumption.

Future Directions

• Expanded Use of AI and Digital Twins: Companies should explore the use of AI and digital twins to enhance energy efficiency in various sectors.
• Integration of AI with Existing Systems: Integrating AI with existing building management systems and IoT hubs can provide real-time data and enhance decision-making.
• Development of Physics-Informed AI Models: Developing physics-informed AI models can help accelerate simulation work and improve thermal dynamics, reducing operational risks.

Recommendations

• Adopt AI and Digital Twins: Companies should consider adopting AI and digital twins to enhance energy efficiency in manufacturing.
• Invest in Training: Companies should invest in training their teams to use AI and digital twins effectively.
• Collaborate with Technology Providers: Companies should collaborate with technology providers like NVIDIA to leverage their expertise in AI and digital twins.

Final Thoughts

The use of AI and digital twins in manufacturing has the potential to revolutionize energy efficiency. Wistron’s success story highlights the benefits of leveraging AI and NVIDIA Omniverse to enhance energy efficiency in manufacturing. As companies continue to explore ways to reduce energy consumption and environmental impact, the use of AI and digital twins will play a crucial role.

Conclusion

Wistron’s use of AI and NVIDIA Omniverse to enhance energy efficiency in manufacturing is a significant step forward in reducing environmental impact and operational costs. By developing a digital twin platform and AI-enabled simulation tools, Wistron has been able to optimize the design, performance, and energy efficiency of their run-in test rooms, potentially saving up to 10% in energy consumption. This success story highlights the potential of AI and digital twins in revolutionizing energy efficiency in manufacturing.