In the story of Investiture of the Gods, after causing a massive disaster, Nezha carved his flesh and returned his bones to his parents, leaving only a wandering and helpless soul. Taiyi Zhenren broke two lotus roots to serve as bones and picked three lotus leaves for clothing, borrowing the spiritual energy of heaven and earth to reshape a lotus incarnation for Nezha. With this physical body capable of fighting and enduring, Nezha was able to return to the mortal world and display his divine powers.
This myth serves as a fitting metaphor for the industrial reality in today's embodied AI field.
Amid the surging wave of large models over the past few years, the humanoid robot sector has spawned numerous intelligent algorithmic souls. Large models have endowed them with common sense understanding and reasoning decision-making capabilities. However, when these robots step out of the laboratory and actually enter factory workshops to screw bolts and move boxes, they frequently encounter bottlenecks in real industrial settings due to insufficient joint precision, limited mechanical rigidity, unstable motion control, and difficulties in adapting to production line processes.
Who will play the role of Taiyi Zhenren today, using solid industrial-grade engineering skills and software-hardware systems to reshape a truly robust physical body for humanoid robots that can actually enter workshops and perform heavy-duty tasks?
At the upcoming 26th China International Industry Fair (CIIF), Siemens has provided its own answer. Facing the widely discussed Physical AI proposition, Siemens' theme for this year's CIIF is "Integration of Digital and Physical Realms, New Intelligent Growth", demonstrating how to forge an industrial-grade physical body for humanoid robots through a full-process solution spanning R&D design, production manufacturing, final assembly integration, and industrial field applications; simultaneously, it uses a full-chain electromechanical engineering solution to build a solid operational foundation for the high-density computing facilities running day and night behind the scenes.
I. Clarifying the Logic of Building Humanoid Robot Bodies
Embodied AI is the most direct landing point for Physical AI in industrial settings. Through environmental perception, autonomous decision-making, and motion control, humanoid robots complete precise handling and complex assembly on real production lines, extending AI from the brain to the limbs and forming a complete action closed loop. However, this body, capable of withstanding harsh industrial conditions, must pass multiple tests in material mechanics, thermal balance, micrometer-level machining tolerances, and production line takt time.
At this year's CIIF, Siemens will, for the first time, comprehensively present the full lifecycle chain of humanoid robots from design, manufacturing, and final assembly to on-site operations to the public, showcasing the underlying industrial logic behind body building in front of the audience.
To endow the limb joints of robots with high load-bearing capacity and precision, the machining of core components is a hard threshold. In the joint actuators of humanoid robots, the most difficult key component to machine is the planetary roller screw, which directly determines the positioning accuracy and service life of the joint. At the exhibition, Siemens showcased a complete solution for machining planetary roller screws based on the SINUMERIK 8282D CNC system. By combining the CNC system core with digital twin technology, virtual commissioning and optimization of the machining process are realized, ensuring high-precision and high-efficiency production.
Tracing back to the R&D and design phase, because humanoid robots pursue compactness and lightness, their bodies are packed with high-power-density motors and drive modules, and long-term high-load operation easily leads to local heat accumulation; moreover, the multi-axis motion balance of dozens of degrees of freedom cannot be tested and verified through repeated prototyping in a handicraft workshop style. Siemens has integrated industrial software environments such as Designcenter, Simcenter, Teamcenter, Opcenter, and ICX, utilizing multi-physics simulation to jointly verify the robot's multi-body dynamics, motion posture, and complex thermal management in a purely virtual environment, significantly reducing the number of physical prototype trials and markedly shortening the R&D cycle.
Moving to the final assembly and production line implementation phase, hundreds or even thousands of components need to be assembled into a qualified humanoid robot, and the balancing and takt time control of the assembly line are equally headache-inducing. Siemens utilizes Process Simulation software to simulate and optimize the complete machine assembly line of humanoid robots, identifying production line bottlenecks in advance and shortening the production ramp-up time. At the booth, visitors will also see humanoid robots undertaking practical tasks such as raw material handling, participating in the production process of their own components, and demonstrating real-world operational capabilities. During the exhibition, Siemens will also officially announce the opening of embodied AI factory application scenarios and gather with robot body manufacturers and component supply chain partners for a roundtable discussion to talk about the hard challenges this technology faces when stepping from the laboratory into industrial workshops.
II. Building the Computing Foundation for Physical AI
Building a good physical body for terminal robots is just one step. The efficient operation of Physical AI also relies on the other half—the high-density computing infrastructure supporting model training and edge inference in the backend.
As computing density surges, data centers have long moved beyond the category of simple server rooms, evolving into complex physical electromechanical systems that consume massive amounts of electrical energy and dissipate astonishing amounts of heat. The ultra-high cooling load, strict power supply stability, and tight engineering delivery cycles constitute another layer of industrial engineering challenge behind Physical AI.
At this year's exhibition, Siemens takes the "Data Center 5.0" architecture as the main thread, presenting full-chain engineering capabilities from virtual simulation and engineering implementation to intelligent operation and maintenance. Facing complex cooling and power supply and distribution architectures, Siemens adopts a "simulate first, build later" approach, using Simcenter software to perform electromechanical and thermodynamic simulations for high-energy-consuming heat exchange processes such as cooling stations, and using the SIMIT platform to conduct control logic simulations for core equipment such as Coolant Distribution Units (CDU) and link them with human-machine interfaces for verification, eliminating control defects in advance; at the same time, it uses COMOS software to complete process flow diagram design and digital delivery, sending engineering drawings and equipment parameters as structured data directly to the owner's operation and maintenance end.
At the physical equipment level, Siemens covers the full-line capabilities from power supply and distribution, power monitoring, cold source control to liquid cooling management, avoiding the protocol disputes and maintenance risks caused by traditional multi-brand patchwork. At the booth, a real physical exhibit of a customer's CDU liquid cooling system is directly brought in, equipped with Siemens SIMATIC S7-1200 PLC, human-machine interfaces, SINAMICS G120XA frequency converters, and process measuring instruments, fully demonstrating the process from virtual simulation to physical operation. In addition, relying on its localized delivery experience in overseas markets such as Southeast Asia, the Americas, and Europe, Siemens provides engineering support for the global expansion of Chinese computing enterprises and engineering contractors.
III. Consolidating the Full-Stack Technology Cornerstone for the Landing of Physical AI
With the physical body for work and the foundation providing computing power, for Physical AI to truly take root and sprout in industrial scenarios, an industrial neural network that closely connects the workshop site with top-level decision-making is also needed. If there is a lack of full-stack software and hardware integration, the massive amount of data collected on-site will be reduced to isolated islands, and cutting-edge algorithms will not be able to be transformed into tangible productivity.
At the core position of the CIIF booth this year, Siemens presents the "Diamond Heart 3.0", which集中 (concentrates on) presenting its full-stack software and hardware capabilities, providing a panoramic display of the complete product family from underlying automation hardware to cloud-based industrial software, covering various industrial scenarios such as discrete manufacturing, process industry, and hybrid applications. This year, this system focuses on demonstrating how AI truly sinks into actual industrial scenarios, providing clear technical answers from three dimensions: intelligence, breadth, and depth.
In the dimension of intelligence, Siemens directly embeds AI capabilities into various levels of industrial operation nodes. At the equipment site level, tools such as ProDiag and DriveTRAIN analyzer are used to conduct real-time intelligent diagnosis of motor drive chains and key equipment; at the operation management level, predictive maintenance analysis is carried out relying on SiePA, combined with the ICX enterprise-level intelligent agent platform for data mining and decision support. At the booth, through real-scene operation and debugging, it intuitively demonstrates how AI helps engineers detect equipment hazards earlier and finalize maintenance plans faster on real production lines.
In the dimensions of breadth and depth, Siemens focuses on full-scenario coverage and vertical data penetration. From economical and practical configurations to complex high-end equipment control, enterprises with different digital foundations can find corresponding solutions. More importantly, Siemens has built a vertical five-layer architecture spanning the site level, control level, operation level, management level, and cloud. The underlying data collected by sensors flows seamlessly to edge computing and cloud software. In the workshop, SiePA can quickly transform equipment edge data into actionable insights for front-line operators to execute immediately; at the enterprise management level, Intelligence Center X and Teamcenter connect global transparency and full lifecycle management, allowing industrial data to flow and增值 (add value) repeatedly across various process links.
However, the upgrade of industrial scenarios has never been a solo show by a few pioneer enterprises. While showcasing cutting-edge AI applications, Siemens also takes into account the fundamental needs of China's manufacturing sector, which is large in volume and wide in scope. During the exhibition, Siemens will also release more than 20 new products, including a new batch of products innovated in China, covering categories such as PLC, distributed I/O, basic frequency converters, and human-machine interfaces. These products are all created using a full-value-chain localization model of local demand definition, local R&D, and local production, which better fits the usage scenarios and cost needs of domestic enterprises. They can provide more cost-effective underlying automation support for various industrial applications, including embodied AI, helping enterprises with different digital foundations lower the threshold for improving quality and efficiency.
Taiyi Zhenren relied on magic and craftsmanship to reshape Nezha's physical body; Siemens relies on a century of industrial manufacturing heritage and engineering capabilities to build the physical body and computing foundation for Physical AI. Today, as AI accelerates its penetration into the physical world, the industrial sector needs not only algorithmic geniuses who can write code but also manufacturing experts who understand materials, processes, and production lines. Therefore, at this year's CIIF, you might as well come and see how Siemens, this century-old industrial giant, uses hardcore craftsmanship to reshape the physical body for future silicon-based workers.