The factory that produces humanoid robots every 30 minutes: they will build cars and home appliances.

On March 29, 2026, a factory in Guangdong, China, commenced operations. Among its capabilities according to its management it can deliver a finished humanoid robot every 30 minutes.

With an estimated annual production of up to 10,000 units, the project aims to transition from small scale experimentation to mass industrial production, set against a global backdrop of accelerating competition in humanoid robot development.

Large-Scale Assembly

The new production line was driven by a collaboration between Leju Robotics and Dongfang Precision Science and Technology. The latter previously known for its packaging equipment for corrugated cardboard has expanded its scope of operations into contract robotics. The facility incorporates 24 stages of precision assembly and 77 inspection checkpoints. This design allows each humanoid robot to be completed in half an hour, boosting efficiency by approximately 50% compared to conventional methods.

The factory features a flexible manufacturing system based on automated guided vehicles and digital control systems. This approach allows for switching between different robot models without altering the line's physical structure a capability that facilitates the fulfillment of diverse orders from industries such as the automotive and home appliance sectors.

Before shipment, each robot undergoes 41 tests simulating real jobs, operating conditions a measure designed to guarantee reliability when these humanoid robots are integrated into industrial processes for continuous operation.

The Contract Manufacturing Model and the Software Challenge

The aforementioned alliance highlights a key trend within the robotics sector: specialization by area. While Leju handles design and software development, Dongfang Precision takes charge of large-scale production, systems integration, and after-sales service. This model aims to overcome one of the primary challenges in robotics: transforming advanced prototypes into reliable machines suitable for mass production.

Dongfang Precision’s stake in Leju Robotics holding a 2.8% interest in the company helps align incentives between the two parties. This type of collaboration accelerates the market deployment of robotic solutions and reflects a broader cooperative model prevalent within the emerging ecosystem of physical artificial intelligence.

Despite advancements in hardware and supply chains, software development remains the critical outstanding factor. The industry faces the challenge of equipping humanoid robots with operating systems robust enough to respond effectively to complex work environments.

Software remains the key challenge, placing pressure on AI developers to transform these machines into useful workers, moving beyond mere technological showcases.

International Competition and Industry Pressure

The launch of the Guangdong plant positions Leju Robotics among the leading global manufacturers of humanoid robots. Other companies are also advancing rapidly: Agibot announced the production of its 10,000th humanoid robot, while Unitree Robotics is driving a $580 million funding campaign to support a facility capable of producing 75,000 units per year.

Meanwhile, UBTECH Robotics aims to reach an annual production volume of 5,000 units and reduce the cost per robot to below $20,000.

In this context, achieving an annual production output of 10,000 units represents both a milestone and a strategic imperative for Leju. In the current humanoid robotics market, manufacturing volume has become a decisive criterion for attracting investment and demonstrating the commercial viability of projects.

The advancement of the Guangdong production line reflects a trend in which manufacturing capacity, reliability in continuous operation, and the ability to rapidly adapt to new models are the factors that define industry leadership. As attention shifts toward software refinement, manufacturers are seeking to consolidate their position in a global race where industrial scale and flexibility serve as key differentiators.

To overcome their dependence on controlled environments and predefined tasks, robots must improve their ability to operate effectively in changing contexts and with diverse objects, without each new function requiring a lengthy retraining process.