Wistron Accelerates and Scales Advanced Manufacturing of AI Infrastructure

One of the most important but challenging aspects of advanced manufacturing is quality control. Wistron’s burn-in test rooms are where NVIDIA AI systems are rigorously stress tested before being shipped and installed in AI factories across the globe. These dynamic environments are critical for ensuring the reliability, quality, and safety of these complex systems, enable early detection of potential issues, and are crucial for compliance with industry standards.

Simulation plays a critical role in helping Wistron’s engineers design, test, and operate these environments.

For years, Wistron’s engineers relied on traditional computational fluid dynamics (CFD) simulations. However, these approaches lacked the flexibility their teams required. The simulations took engineers too long to set up and complete, and when operational parameters changed they had to rerun them from scratch, resulting in operational delays and unnecessary energy waste.

To solve this, Wistron integrated NVIDIA PhysicsNeMo—an open source framework for building physics-informed AI models—into its digital twin platform. Now, Wistron engineers use these AI-physics-driven digital twins, alongside the Cadence Reality Digital Twin Platform, to conduct close to real-time simulation studies of their quality control processes and environments—accelerating their workflows from 15 hours to seconds—a 15,000x speedup.

Equally, the inspection of manufactured and assembled products is a key priority for Wistron’s operations teams. One of the industry’s most persistent bottlenecks is the scarcity of real-world data to train high-quality inspection models.

To address this for its surface mounting technology (SMT) production lines, Wistron has deployed NVIDIA Cosmos world foundation models. Using the NVIDIA Defect Image Generation skill—powered by Cosmos and NVIDIA TAO—its engineers use images from real production to generate high-fidelity training data at scale. A manual process that previously took its teams many hours, now takes seconds. 

When integrated into Wistron’s automated optical inspection workflows, this closed-loop synthetic data pipeline eliminates annotation costs, improves defect detection accuracy by 5%–20%, and establishes a replicable framework that can be rapidly adapted as new product designs and defect types emerge.

Wistron’s digital twin platform has now become a smart operating system for its global manufacturing sites. 

Inside Wistron factories, thousands of sensors monitor operations, from core temperatures to air conditioning return temperatures and inlet temperatures. These real-time systems are now connected to the company’s digital twin platform, enabling its global operations teams and managers to monitor and manage operations from anywhere. When issues arise, engineers can digitally reconstruct exactly what happened on the production floor at any given moment.

The digital twin continuously analyzes power consumption, thermal flow, and equipment status in real time. It uses AI models to predict temperature changes, allowing teams to make adjustments to energy allocation and testing schedules, prevent operational issues, and ensure cooling systems perform at peak efficiency. 

This shift to real-time simulation and AI-driven operations has contributed an estimated 10% reduction in total energy consumption across Wistron facilities.

In addition to its digital twin platform, Wistron is building, deploying, and orchestrating AI agents to support factory operations teams with real-time automated quality control and root-cause analysis on the production line—using NVIDIA Nemotron and Cosmos models, Metropolis VSS Blueprint, and NemoClaw™ for secure agent runtimes. 

To scale these agents across systems and facilities, Wistron is building its ‘Factory Brain’—powered by the NVIDIA Factory Operations Blueprint (FOX). The factory brain will perform multi-agent orchestration, spanning equipment monitoring, anomaly analysis, process optimization, and quality control, giving Wistron teams factory-wide visibility to make faster, better-informed decisions.

It doesn’t stop there. The digital twin platform and these agents are also helping Wistron managers and team leads onboard and train new factory workers, including new employees in its Texas factory. AR and VR training using Apple Vision Pro guides them through complex assembly procedures with step-by-step digital guidance—enabling self-paced learning at scale, without requiring expert supervisors on the floor for every shift.

From designing and validating its latest Fort Worth facility in simulation, to deploying digital twins and agents across its factories, Wistron’s technology innovation and commitment to quality and sustainability is providing a blueprint for other manufacturers. And its advanced manufacturing leadership is helping shape the next industrial revolution.

The new U.S. factory strengthens the AI infrastructure supply chain by expanding domestic capacity to assemble and test NVIDIA AI systems. These server building blocks can be integrated into NVIDIA DSX infrastructure, while DSX provides the common architecture, software, and partner technologies needed to deploy and operate that infrastructure at scale.

With every accelerated AI system produced and tested in its factories, countries, companies, and individuals—from students and researchers to engineers and scientists—can reimagine what’s possible and solve challenges previously out of reach.

To learn more, check out Wistron’s GTC session on demand.