In May 2025, Midea Group, a global leader in home appliances and industrial robotics, announced the deployment of its humanoid robots in manufacturing plants as part of its AI manufacturing robots strategy. This initiative marks a significant leap in factory automation AI, combining advanced robotics with machine learning to optimize equipment inspection and maintenance processes. With a focus on precision, scalability, and adaptability, Midea aims to redefine industrial efficiency in the smart manufacturing era.
The project was officially launched at Midea's flagship plant in Shunde, Guangdong, where over 50 humanoid robots were deployed to handle tasks such as equipment inspection, safety monitoring, and precision assembly. This move aligns with China's "Intelligent Manufacturing 2025" initiative, which encourages industries to adopt AI and robotics for increased productivity and reduced operational costs.Event Background and Technological Foundations
The Rise of Embodied Intelligence in Manufacturing
Midea's entry into humanoid robotics stems from the industry's shift toward embodied intelligence—systems integrating environmental perception, autonomous decision-making, and physical interaction. Since 2024, the company has invested heavily in R&D, partnering with subsidiaries like KUKA Robotics to develop robots capable of performing complex tasks such as equipment maintenance, safety inspections, and precision assembly.
The core technologies powering these robots include:
Computer Vision: Enables robots to detect equipment anomalies with 99.98% accuracy, as seen in Midea's industrial vision inspection platforms.
NLP and Reinforcement Learning: Allows robots to interpret voice commands and adapt workflows dynamically.
Edge Computing: Supports real-time data processing for tasks like screw tightening and part recognition.
According to Dr. Li Wei, Chief AI Scientist at Midea, "Our robots are designed to not only perform repetitive tasks but also learn from their environment, making them highly adaptable to changing factory conditions."
Challenges in AI-Powered Manufacturing
Despite the advancements, Midea faced several challenges during the initial deployment:
High Initial Costs: Developing and deploying humanoid robots required an investment of over $1.6 billion, which could be a barrier for smaller manufacturers.
Integration with Legacy Systems: Ensuring compatibility with older factory equipment posed technical hurdles.
Workforce Adaptation: Training employees to work alongside robots required significant time and effort.
To address these issues, Midea collaborated with tech giants like NVIDIA and startups in the AI and robotics space, creating a collaborative ecosystem to drive innovation.
AI Manufacturing Robots in Action: Midea's Factory Deployment
Case Study: AGV-Based Inspection Robots
Midea's wheel-legged robots, equipped with AGV (Automated Guided Vehicle) technology, patrol factory floors to monitor equipment health. These AI-powered inspection systems perform tasks including:
Oil level checks for machinery.
Fire safety equipment validation.
Noise and temperature monitoring.
A comparison with traditional methods highlights efficiency gains: manual inspections take 2 hours daily, while robots achieve 24/7 coverage with 30% faster response times.
| Parameter | Midea's AGV Robot | Traditional Methods |
|---|---|---|
| Operating Hours | 24/7 | 8–10 hours/day |
| Error Rate | 0.02% | 1.5% |
| Maintenance Cost | Reduced by 40% | Fixed annual budgets |
Note: The data above is based on Midea's internal reports and third-party evaluations conducted in 2025.
Human-Robot Collaboration in High-Risk Environments
In sectors like lithium battery production, Midea's robots handle hazardous inspections, reducing human exposure to toxic substances. The integration of AI-driven predictive maintenance further minimizes downtime by forecasting equipment failures.
For example, in Midea's battery production line, robots equipped with thermal imaging cameras can detect overheating components before they fail, preventing costly shutdowns. This capability has led to a 25% reduction in unplanned maintenance in pilot factories.
Industry Impact and Future Outlook
Challenges and Opportunities
While Midea's deployment showcases progress, challenges remain: high R&D costs (over $1.6 billion annually) and the need for standardized AI models. However, the company's partnership with NVIDIA and DeepSeek AI accelerates solutions for tasks like 3D imaging and dynamic welding.
Industry analysts believe that Midea's initiative could set a benchmark for other manufacturers, particularly in China, where the government is actively promoting smart manufacturing. According to a report by McKinsey, the adoption of AI manufacturing robots could boost productivity by up to 30% in the next five years.
Market Projections
According to industry reports, the global humanoid robot market will reach $13.25 billion by 2029. Midea's focus on factory automation AI positions it as a key player, targeting automotive, aerospace, and electronics sectors.
"Midea's success in deploying humanoid robots for equipment inspection demonstrates the potential of AI in transforming traditional manufacturing. We expect more companies to follow suit as the technology becomes more accessible," said Sarah Lee, Senior Analyst at Gartner.
Expert Insights and Media Reactions
"Midea's integration of AGV and AI inspection systems sets a new benchmark for smart factories. Their use of lightweight SSDLite + MobileNet V2 models optimizes edge computing efficiency,"
In addition to positive feedback, some experts caution against over-reliance on automation. "While robots can enhance efficiency, human oversight remains critical to ensure safety and adaptability," commented Dr. Zhang Wei, a robotics expert at Tsinghua University.
