Build an upgraded version of intelligent manufacturing
Our reporters Lai Qichun and Huang Xin
Industrial upgrading centered on smart manufacturing is the core leverage and strategic fulcrum that determines the quality and competitiveness of the modern industrial system. At the recent 2026 CCID Forum, Su Bo, Deputy Director of the National Advisory Committee for Building a Strong Manufacturing Nation and Director of the National Expert Committee on Smart Manufacturing, stated that China has clearly taken smart manufacturing as its main focus, gradually forming a distinctive path of parallel advancement in digitalization, networking, and intelligence, successfully achieving the "first step" strategic goal of building a strong manufacturing nation. The overall level of the manufacturing industry has shifted from being dominated by mid-to-low-end products to being among the mid-to-high-end in multiple important fields, with 5G communication equipment, high-speed rail equipment, shipbuilding, new energy vehicles, wind power, and solar power generation equipment reaching world-leading levels.
By the end of last year, China's coverage rate of digital transformation for industrial enterprises above designated size had reached 89.6%, and the penetration rate of digital equipment had reached 57.7%. As an important carrier of smart manufacturing, the production and sales of industrial robots in China exceeded the total of other countries.
The core technological innovation capability has been continuously enhanced, and the supply capacity of intelligent manufacturing has been significantly improved. In terms of core technological breakthroughs, breakthroughs have been made in the system solutions for the "new three products" of photovoltaic, power batteries, and electric vehicles. In terms of information infrastructure construction, China has cultivated more than 340 influential industrial internet platforms, with key platforms connecting over 100 million industrial equipment units (sets), serving approximately 4 million enterprises, and industrial internet applications covering 49 major categories of the national economy. In terms of talent team building, nearly 500 undergraduate majors related to intelligent manufacturing have been launched, and comprehensive cooperation and collaborative education in the field of intelligent manufacturing have been carried out.
With the deep integration of artificial intelligence and manufacturing, new models and formats of smart manufacturing are continuously evolving from "point breakthroughs" to "flowering on a large scale". Haoyang Environmental Co., Ltd., relying on the Inspur Haiyue industrial software system, has built an integrated data control and cost management platform. Through the deep integration of technology and management, it has addressed the pain points of traditional manufacturing, achieving a reduction of over 5% in raw material loss rate and production cost, a data accuracy rate of over 95%, a 20% increase in production efficiency, a 15% reduction in labor costs, and providing replicable experience for the digital transformation of the environmental protection industry.
"Smart manufacturing promotes the development of industrial production towards distributed, non-standardized, and customized directions, thereby achieving large-scale personalized customization. This not only significantly improves production efficiency but also enables precise control over process flow and energy consumption, driving the green transformation of manufacturing methods," said Wang Yiming, former Deputy Director of the Development Research Center of the State Council.
At the 11th plenary session of the State Council held on March 16, "accelerating the development of a new generation of intelligent manufacturing" was listed as a key task that needs to be well addressed. In Su Bo's view, the "newness" of the new generation lies in its autonomy. This means that product development will rely more on virtual simulation, generative design, and digital twins; manufacturing will accelerate the formation of a closed loop of "sensing-decision-making-execution-feedback"; factory operations will rely on factory operating systems, industrial software, industrial internet, and computing facilities to achieve full process integration; Wait.
Su Bo stated that in the future, China will continue to adhere to the main direction of smart manufacturing without wavering, and strive to create an upgraded version of smart manufacturing that combines virtual and real worlds, evolves autonomously, and is safe and efficient. By 2030, it is expected that digital and networked manufacturing will be basically popularized among manufacturing enterprises above a certain size, and the new generation of smart manufacturing innovation and research will achieve phased progress. By 2035, it is expected that digital, networked, and intelligent manufacturing will be basically popularized among manufacturing enterprises above a certain size, and the application of new generation smart manufacturing technology will be at the forefront of the world.
It should also be noted that China faces numerous practical bottlenecks in developing a new generation of intelligent manufacturing. For instance, while the technical concepts are well understood, their practical application in the workshop is still limited; application scenarios can be piloted, but replication and promotion are challenging; enterprises have the willingness to transform, but they either cannot, cannot afford, or dare not make the transition. Experts indicate that the underlying reasons lie in the insufficiently systematic accumulation of industrial knowledge, scattered industrial data, the lack of true integration between software models and equipment, and the continued shortcomings in key core technologies and high-end supply.
"The key to the next step is to focus on the problems, address the shortcomings, and implement policies and measures where they are most needed," Su Bo said.
Wang Yiming believes that achieving intelligence is an inevitable choice to adapt to the new technological revolution. It is necessary to implement the "Artificial Intelligence+" initiative and promote the transformation and upgrading of traditional industries through AI empowerment. Focusing on smart manufacturing, we should build smart manufacturing units, intelligent production lines, smart workshops, and smart factories. Implement the "Industrial Internet Innovation and Development Project", expand the coverage of industrial perception networks, and create massive IoT access capabilities. Promote the construction of the industrial internet identification system and the formulation of standards and norms, accelerate the promotion of typical application scenarios, and enhance the industry empowerment capability of the industrial internet.
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