What does Liaoning’s shift toward intelligent manufacturing mean?

What the Shift Toward Intelligent Manufacturing Means for Liaoning

Liaoning is reinterpreting the label of “old industrial base” as a “large manufacturing platform that can be digitally transformed.” From provincial-level planning to specific process upgrades in individual factories, the core of this change is not simply improved efficiency, but the restructuring of the manufacturing system itself: who controls the pace of production, who masters process data, and who decides the future value added of industry.

In the direction outlined in Liaoning’s latest 15th Five-Year Plan, intelligence, green development, and integration are placed within the same framework. This combination is not new, but in Liaoning’s industrial structure, its meaning is especially clear. Here there are petrochemicals and metallurgy, as well as equipment manufacturing and automotive production; there are both long-chain heavy industries and many production scenarios that are highly process-intensive and heavily reliant on labor. In other words, Liaoning’s challenge is not whether it has industries, but whether these industries can shift from experience-driven to data-driven operations.

This is also why Liaoning has made artificial intelligence, big data, and the industrial internet key levers for manufacturing transformation. For a province with a deep industrial foundation but still a relatively high share of traditional industries, digitalization is not an embellishment; it is the only practical path to turning existing industrial capacity into incremental capability. The real change lies in manufacturing competition shifting from advantages in capacity, equipment, and labor to process digitalization, flexible organizational capability, and cross-factory coordination efficiency.

The case of Fushun New Steel illustrates this point. In the past, fuel composition testing relied on manual operations by laboratory technicians, with nearly 1,000 weighings and data entries each day, making the process cumbersome and limiting efficiency. After intelligent and digital transformation, sample transfer and testing became automated, the testing cycle was shortened by 40%, overall efficiency increased by 15%, and human error was significantly reduced. On the surface, such improvements are about “reducing headcount,” but at a deeper level, they are about “shifting process judgment from human experience to systematic workflows.” In the steel industry, once testing, batching, and quality control are digitalized, both the cost curve and stability change.

The steel industry is the most representative entry point for Liaoning’s manufacturing transformation. The color-coated production line at Ansteel’s cold rolling plant has already achieved one-button startup and unmanned operation, boosting production efficiency by about 20% and reducing production costs by nearly 10%. This means steel companies are moving from the traditional model of “heavy assets, heavy energy consumption, and heavy labor” toward refined manufacturing based on automatic control and process optimization. For China’s steel industry, the significance of this change is no less than capacity adjustment itself. Future competition will not only be about who can produce more steel, but who can deliver high-end sheet products and deep-processing products with lower volatility, higher consistency, and less energy consumption.What is more noteworthy is that Liaoning has not confined its transformation to a single enterprise; instead, it is building a regional ecosystem oriented toward industrial scenarios. The province has already formed an overall framework supported by 23 national-level 5G factories, 2 national-level industrial Internet platforms, and 4 national-level transformation pilot cities. This means that what Liaoning is trying to solve is not the automation problem of any one factory, but the connectivity problem of the entire industrial network. For manufacturing, upgrading individual equipment can only bring localized efficiency gains; what can truly enhance regional industrial competitiveness is systematic transformation driven jointly by platforms, data, standards, and talent.

BMW Brilliance’s Tiexi plant offers another model. Digital twin technology allows employees to master production skills in a virtual environment, and the factory has also launched the “Digital Pioneer” program to improve the digital capabilities of thousands of production engineers. The transformation of automotive plants is especially telling of Liaoning’s future direction: if the digitalization of steel and equipment manufacturing is mainly about improving process efficiency, then the digitalization of automobile manufacturing is about building flexible production and rapid iteration capabilities. As new energy vehicles and smart vehicles continue to reshape supply chains, competition among complete vehicle and parts plants is increasingly dependent on whether factories can quickly adapt to new models, new processes, and new quality standards.

Liaoning’s industrial reality determines that it cannot talk only about “upgrading”; it must also talk about “undertaking.” The high share of traditional industry here means there is plenty of room for transformation, but it also means high transformation costs, complex pathways, and strong organizational inertia. The province’s proposal to achieve full coverage of intelligent and digital transformation for industrial enterprises above designated size by 2028 is, in effect, bringing this issue into the schedule and assessment mechanism. For local governments, this goal-setting is not only industrial policy, but also a reshaping of local industrial governance: through nine support policies such as fiscal subsidies, interest discounts on loans, and financial services, it turns enterprises’ willingness to transform into investment behavior.

From the perspective of the industrial chain, Liaoning’s significance lies not only in improving local industrial efficiency, but also in its potential to affect the technology diffusion path of heavy industry in Northeast China and even the whole country. Industries such as equipment manufacturing, steel, and petrochemicals are often regarded as “mature industries,” but precisely because their processes are mature, their production lines are complex, and their asset scales are large, they are better suited to become high-value scenarios for industrial Internet and AI applications. Once Liaoning forms a replicable transformation model, demand across the supply chain for sensors, industrial software, automation control, 5G private networks, industrial robots, and digital twins will expand accordingly.

This change will also alter the logic of regional industrial competition. In the past, industrial cities competed on land, energy, and tax incentives; going forward, competition will be about computing infrastructure, industrial software service capabilities, talent supply, and systems integration capabilities. A responsible official in Liaoning has noted the need to strengthen the “dual-core” driving role of Shenyang and Dalian and to reinforce new infrastructure such as computing power, which makes the direction very clear: manufacturing digitalization is not an isolated project, but one that requires the joint support of urban clusters, industrial parks, and technical service systems.From a national perspective, Liaoning’s transformation represents an important type of upgrade in China’s manufacturing sector: not building new industries from scratch, but reorganizing an existing industrial system. It differs from the “new track” expansion of photovoltaics, energy storage, or new-energy vehicles, and it also differs from hard-tech breakthroughs driven purely by R&D. Instead, it reinserts traditional pillar industries such as steel, equipment, and automobiles into digital infrastructure. This kind of upgrade is slower, but once completed, it brings not just a rise in output value for a single industry, but a reassessment of productivity across the entire industrial system.

This also explains why Liaoning’s smart manufacturing is not just a local news story. It reflects one of the most important questions in the next stage of China’s manufacturing development: on the basis of a large-scale industrial foundation, how can digitalization and intelligentization transform traditional capacity into high-quality capacity? For supply chains, this means a more stable delivery rhythm, more controllable quality, and more flexible factory collaboration; for the industrial landscape, it means that old industrial bases are no longer merely historical legacies, but may once again become key nodes in China’s high-end manufacturing system.