Dinghe Think Tank | Only 15 in the country! The “national template” for traditional industrial upgra
On November 27th, six departments, including the Ministry of Industry and Information Technology, announced the first batch of 15 leading smart factories, covering key industries such as equipment manufacturing, raw materials, and electronic information. These 15 factories not only represent the "ceiling" of intelligent manufacturing in my country, but also provide a replicable and implementable "standard answer" for upgrading traditional industries that are deeply mired in transformation anxiety.
What makes upgrading traditional industries so difficult? Simply put, it's a lack of technology, a lack of clear strategies, and a fear of wasting investment. The success of these pioneering smart factories precisely breaks down the core logic of industrial upgrading, addressing the pain points of traditional industrial transformation at every step, from technological integration to ecosystem co-construction. Today, we'll analyze how to replicate the core experiences of this "national model."
List of the first batch of 15 leading smart factories by 2025
First, understand: What makes the "national model" so great?
Being selected as a leading smart factory is not simply a matter of "replacing humans with machines," but rather a comprehensive breakthrough in technology, management, and the industrial chain. This is the core reason why it can become a "model."
According to the "Conditions for the Gradual Development of Smart Factories (2025 Edition)," smart factories are divided into four progressive levels, as detailed in the table below:
First, the technological integration has achieved "deep coupling".Leading-level factories require AI technology to be applied in at least 60% of their operations, far exceeding the 20% requirement for superior-level factories. They must also integrate industrial internet, digital twins, and computing infrastructure. For example, Nanjing Iron & Steel uses digital twins and AI to customize special steel, achieving a 98.5% on-time order rate and halving the R&D cycle. XCMG Machinery, on the other hand, uses AI to drive R&D and manufacturing, shortening order delivery cycles by 55%. This technology is not merely a superficial application, but rather integrated into every aspect of production, R&D, and management.
Secondly, the management model has come up with "new tricks".These factories have created "intelligent operation management systems" that enable processes such as marketing and supply chain management to be automated or even unmanned, achieving "zero waste, zero inventory, and zero emissions" in the production process. For example, Gree Electric's full value chain collaborative factory has achieved intelligent control over the entire process from design to after-sales service, which is precisely the refined management capability that traditional industries lack most.
Finally, the industrial chain achieved "large-scale collaboration".Leading-edge factories don't operate in isolation; instead, they leverage a "parent factory + replication and promotion" mechanism to drive the upgrading of upstream and downstream SMEs. For example, SAIC-GM-Wuling's island-style intelligent factory shares its experience in process decoupling and production line restructuring with supporting enterprises, forming a regional intelligent manufacturing ecosystem.
Key takeaways: 3 core approaches to replicating experience
Traditional industrial enterprises vary in size and foundation, making it impossible to directly copy the complete model of a leading factory. However, these three core approaches are applicable to all enterprises that want to upgrade.
Tip 1: Take it step by step, don't try to do everything at once.
The Ministry of Industry and Information Technology has long provided a four-tiered development system for smart factories: basic, advanced, excellent, and leading. This is precisely an "upgrade roadmap" for traditional industrial enterprises.
Small and medium-sized enterprises (SMEs) shouldn't aim for the "leading level" from the outset. They should start with the basics, transitioning from simply having equipment to using data—for example, installing sensors on older equipment and establishing simple production data ledgers to ensure that production processes have "data to view." Once this foundation is established, they can then move towards the advanced level, achieving system collaboration between workshops and departments, such as breaking down data barriers between production and sales. Leading enterprises, on the other hand, can target the excellent and leading levels, focusing on deep AI applications and globally leading technical indicators.
This gradual approach avoids wasting resources due to blind investment and is the common growth path for the 15 leading factories.
Second approach: Don't try to learn too many technologies at once; focus on the "core aspects" first.
The integration of technologies in a leading factory may seem complex, but the core is to "find pain points around the business" rather than simply piling up technologies.
Traditional industrial enterprises can start by focusing on their core business segments: for example, manufacturing companies can optimize production processes by using AI for equipment failure prediction and digital twins to simulate production line upgrades; while manufacturing companies can upgrade their R&D and design processes by using digital tools to shorten new product development cycles. Nanjing Iron & Steel Group (Nanjing Steel) made a breakthrough by starting with the production of customized special steel and then gradually expanding to full-chain collaboration. This approach of "breaking through at a single point and then expanding comprehensively" is far more efficient than "spreading out in all directions."
At the same time, enterprises can leverage external resources—such as collaborating with smart manufacturing solution providers—to reduce the cost of independent R&D, which is also the "supply-empowerment" direction that the government is promoting.
Thirdly, follow the leading enterprises and build a sound industrial ecosystem.
For small and medium-sized enterprises, upgrading alone is too costly; "upgrading together" with industry leaders is the shortcut.
Leading factories bear the mission of driving the industrial chain. For example, equipment manufacturing giants like XCMG and Zoomlion are already sharing their experience in building smart factories. Small and medium-sized enterprises (SMEs) can proactively connect with these "mother factories" to benefit from their technology spillover and order collaboration, such as learning from the leading companies' supply chain management models and accessing their industrial internet platforms. Meanwhile, leading enterprises can also build industry alliances to unify the digital standards of upstream and downstream companies, forming a mutually beneficial smart manufacturing ecosystem.
Dinghe Observation
Upgrading traditional industries is never an "optional" question, but a "mandatory" one. The emergence of these 15 leading smart factories not only showcases the highest level of Chinese manufacturing but also points the way for all traditional industrial enterprises.Upgrading is not about "throwing money at it," but about finding the right methods and choosing the right path.
From basic datafication to deep intelligence, from the upgrading of individual enterprises to the collaboration of the entire industrial chain, the core of this "national model" has never been "to build the most advanced factory", but "to make the upgrade that is most suitable for oneself".
What challenges has your company encountered in industrial upgrading? Is it a lack of technology or a lack of ideas? Share your thoughts in the comments section, and let's find solutions together!
Information source:
[1]CNR.cn，Only 15 companies nationwide made the list! Why do they represent the highest standards?2025-11-29.
[2]Ministry of Industry and Information Technology website，Notice from Six Departments on Launching the 2025 Smart Factory Tiered Cultivation Action.2025-06-24.
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