Shanghai releases a new-generation intelligent manufacturing action plan, proposing to cultivate 500 advanced-level smart factories by 2028

"Shanghai Action Plan for Accelerating the Development of Next-Generation Intelligent Manufacturing" Source: Shanghai Municipal Commission of Economy and Informatization Release date: 2026-10-27 19:10 AI policy-generated poster. Next-generation intelligent manufacturing is an advanced production mode formed by the deep integration of artificial intelligence and manufacturing.

Next-generation intelligent manufacturing is an advanced production mode formed by the deep integration of artificial intelligence and manufacturing. In order to thoroughly implement the national strategic deployment for developing next-generation intelligent manufacturing and to promote the intelligent transformation and upgrading of all factors, all links, and all processes of the manufacturing industry, this action plan is formulated.

I. Overall Goals

By 2028, achieve full coverage of smart factories among key manufacturing enterprises citywide, promote full coverage of the popularization of AI applications in smart factories, cultivate 500 advanced-level smart factories, achieve breakthroughs in more than 2,000 AI application scenarios in manufacturing, develop 10 advanced and applicable vertical-domain large models, launch more than 300 high-level intelligent agents, build new-type infrastructure that meets the needs of next-generation intelligent manufacturing, reach an industrial robot density of 600 units per 10,000 people, promote the entry of 8,000 humanoid robots into factories, drive the scale of the AI-empowered new-type intelligent manufacturing equipment industry to exceed 200 billion yuan, reach a scale of 100 billion yuan for the intelligent manufacturing system integration industry, and accomplish the "54321" goals.

"54321" Goals for Next-Generation Intelligent Manufacturing

Core carriers: Accumulatively cultivate 500 advanced-level smart factories, 50 excellence-level smart factories, and 5 navigator-level smart factories.

Tiered cultivation: Form a four-tier smart factory cultivation system with clearly distinguished basic, advanced, excellence, and navigator levels.

Supply system: Build a three-tier ladder of next-generation intelligent manufacturing comprehensive service providers according to the categories of "single-point implementation, system integration, and intelligence-leading."

Public platforms: Build two major service platforms: an intelligent manufacturing supply-demand matching platform with powerful functions and global reach, and an intelligent manufacturing going-global empowerment platform.

Pilot-scale testing and validation: Establish one intelligent manufacturing pilot-scale testing and validation platform equipped with functions such as intelligent manufacturing equipment validation, industrial large model testing, and standards compliance testing.

II. Implement the Next-Generation Intelligent Manufacturing Supply Leadership Project

(1) Make breakthroughs in core technologies and basic components. Focusing on common fields in the key links of intelligent manufacturing—"perception-control-execution-interconnection"—strive to overcome core technologies such as distributed sensing, multimodal fusion governance, high-dynamic motion planning and control, ultra-precision machining process improvement, industrial wireless real-time communication, and edge intelligence integration. Focus on breakthroughs in basic components such as high-end sensors, high-torque-density servo motors, high-precision heavy-load joint modules, high-performance servo drives, and high-reliability reducers.

(2) Develop and promote new-type intelligent manufacturing equipment. Support the deep integration of AI technology and equipment, and promote the upgrading of intelligent manufacturing equipment into equipment intelligent agents. Develop and promote physical AI equipment, and develop intelligent manufacturing equipment such as robots, industrial machine tools, and testing equipment with autonomous perception and decision-making capabilities, using the demand for smart factory construction to drive equipment upgrading and large-scale application. Support innovative breakthroughs in robots such as humanoid robots, collaborative robots, and high-precision heavy-load robots; accelerate the iterative upgrading of AI-empowered industrial machine tools such as ultra-precision grinding machines, large five-axis machine tools, and high-speed dual-five-axis mirror milling machines; and promote the establishment of independent capabilities in testing equipment such as X-ray photon energy spectrometers, residual gas mass spectrometers, and industrial CT.

(3) Accelerate the creation of industrial intelligent control systems. Strengthen technological breakthroughs in high-performance fault-tolerant runtime engines, large-scale node concurrent processing, and other technologies, and improve supporting capabilities such as protocol stacks, data middleware, standardized interfaces, and dynamic tools. Accelerate the creation of high-level intelligent control products such as programmable logic controllers (PLCs), distributed control systems (DCS), supervisory control and data acquisition systems (SCADA), and safety instrumented systems (SIS). Focusing on key industries such as automobiles, high-end equipment, and new materials, guide enterprises to advance industrial control system upgrades in stages and create typical applications.

(4) Build next-generation intelligent manufacturing service providers. Strengthen the cultivation of next-generation intelligent manufacturing service providers through scenario opening. Promote the intelligent upgrading of producer services such as R&D and design, quality inspection, and supply chain services. Cultivate single-point implementation service providers in areas such as corpus services, digital twins, and AI Agents; cultivate system integration service providers with full-domain connectivity capabilities across processes, equipment, and software and capable of cross-link innovation; strengthen original leadership in industrial AI, and cultivate intelligence-leading service providers that understand processes, equipment, software, and AI. Support manufacturing enterprises in enhancing comprehensive "product + service + solution" capabilities and developing new models and new forms of service-oriented manufacturing.

III. Implement the "AI + Manufacturing" Foundation-Building Innovation Project

(5) Consolidate industrial network and computing infrastructure. Support manufacturing enterprises in carrying out new-type industrial network transformation and promote the integrated evolution of control systems, industrial networks, and computing facilities. Advance pilot programs for industrial 5G/EUHT independent private networks, and support the deployment of high-quality networks such as 5G-A and 10-gigabit optical networks. Accelerate breakthroughs in high-performance AI chips. Accelerate the construction of a "hub-region-edge" computing facility system. Strengthen the coordinated scheduling of intelligent computing resources, accelerate the construction of national computing interconnection nodes, and promote standardized access to and on-demand use of computing resources. Advance actions for inclusive supply of computing services and promote the upgrading and efficiency enhancement of industrial intelligent computing cloud platforms.

(6) Build a new engine for empowering industry with industrial models. Develop more than 10 vertical-domain large models for industries such as high-end equipment, shipbuilding and marine engineering, and industrial software, and improve the ability of large models to understand physical laws, industrial drawings, time-series data, code, and the like; launch more than 300 intelligent agents or specialized models for high-value scenarios such as aided design, adaptive production adjustment, and predictive maintenance; and build a multi-level industrial model system to improve the efficiency of collaboration between large and small models. Guide smart factories to take the lead in carrying out pilot applications of industrial models, and promote the application of models across the entire chain of R&D and design, pilot testing and validation, production and manufacturing, marketing services, and operations management.

(7) Build high-value industrial datasets and specialized service platforms. Support manufacturing enterprises in collaborating with service providers, universities, and research institutes to transform process mechanisms and expert experience into industrial knowledge bases and knowledge graphs with unified heterogeneous process semantics. Strengthen technical breakthroughs in data synthesis, semantic alignment, multimodal fusion, and other technologies, and establish 10 municipal-level high-quality manufacturing data consortia focused on high-end equipment, electronic information, nuclear power, and other fields. Build high-quality industrial datasets with complete structures, accurate annotation, and model adaptability, and, focusing on experience-intensive scenarios such as design review, defect determination, and equipment diagnosis, accumulate 10 categories of "master craftsman" experience datasets. Promote the construction of a general-purpose and specialized integrated industrial corpus service platform.

(8) Promote integrated innovation of artificial intelligence and industrial software. Promote the evolution of traditional industrial software into software agents, and promote the deep application of software agents in the core links of production and manufacturing. Support manufacturing enterprises in opening up scenarios, encourage AI and software enterprises to collaborate with universities and research institutes, and build chain-style application scenarios around R&D and design, production control, equipment operation and maintenance, quality inspection, and the like. Implement the "Hundred Enterprises, Hundred Projects" initiative for AI + industrial software, focus on directions such as the development of AI-native industrial software and AI-enabled intelligent upgrading of industrial software, and carry out collaborative technical and product breakthroughs.

(9) Strengthen industrial cybersecurity protection capabilities. Carry out cybersecurity attack-defense drills and emergency response drills, and enhance the ability to respond to cybersecurity incidents. Promote the implementation of AI security products such as security large models and security agents in the manufacturing industry, build 10 benchmark scenarios such as intelligent penetration testing and AI security operations centers, launch 20 cybersecurity products that deeply apply large models, and build a new protection paradigm of "using models to govern models." Promote more than 10% of high-quality industrial enterprises to achieve classified and graded management of industrial internet security. Strengthen classified and graded data management and security protection, and promote more than 50 high-quality enterprises to carry out work such as important data identification, graded protection, and risk assessment.

IV. Implement the project for tiered cultivation of smart factories

(10) Build basic-level smart factories with broad coverage. Guide manufacturing enterprises to reasonably deploy necessary intelligent manufacturing equipment, software, and systems, and achieve real-time collection of core data, automation of key production processes, and informatization of production and operations management. Each district shall promote manufacturing enterprises in its region to carry out "self-assessment and self-construction" work for basic-level smart factories. By 2028, the cumulative number of basic-level smart factories shall reach 1,600.

(11) Build advanced-level smart factories systematically. Promote basic-level smart factories to widely deploy intelligent manufacturing equipment, software, and systems, achieve interoperability and sharing of production and operation data, precise control of key production processes, and coordinated control of production and operations, aim at typical scenarios to accelerate AI application, form regional demonstrations, and accelerate upgrading to advanced-level smart factories. Each district shall establish a "potential pool" of advanced-level smart factories. By 2028, the cumulative number of advanced-level smart factories shall reach 500.

(12) Build excellence-level smart factories through integrated optimization. Promote advanced-level smart factories to carry out comprehensive optimization across the entire product life cycle and all links of the supply chain, promote multi-scenario system-level applications, achieve integrated and connected design, production, and operation data, intelligent control of manufacturing equipment, and online optimization of production processes, deepen multi-scenario collaborative application of AI, and steadily leap toward excellence-level smart factories. By 2028, the cumulative number of excellence-level smart factories shall reach 50.

(13) Build leading-level smart factories as benchmarks. Promote excellence-level smart factories to accelerate the deep integrated application of vertical-domain models and industrial agents, explore future manufacturing models, drive changes in industrial models and enterprise forms, and strive to advance toward leading-level smart factories. Guide leading-level smart factories to export new technologies, new processes, new equipment, and new models externally, and lead changes in R&D paradigms, production methods, service systems, and organizational structures. By 2028, cultivate a cumulative total of 5 leading-level smart factories.

(14) Expand scenario innovation and application at scale. Focus on the entire links of R&D and design, production and manufacturing, operation and maintenance services, marketing services, supply chain management, and the like, and, in accordance with "single-scenario pilots, multi-scenario integration, and factory-level reconstruction," promote a 100% AI penetration rate in basic-level smart factories, and make the proportion of AI application scenarios in advanced-level, excellence-level, and leading-level smart factories reach 10%, 30%, and 70%, respectively, with AI application scenarios in smart factories exceeding 2,000, and promote effective improvement in enterprise production efficiency and steady shortening of R&D cycles.

(15) Build "AI + Manufacturing" model enterprises. Build 10 "AI + Manufacturing" model enterprises characterized by high-density distribution of agents and multi-scenario integration, launch landmark intelligent production lines and landmark intelligent products, promote the entry of humanoid robots into factories, explore paths to change the underlying logic of manufacturing and achieve qualitative and efficiency leaps, and form industry-wide demonstrations of full-process digital and intelligent transformation that can be replicated and promoted.

V. Implement the project for fostering a new-generation intelligent manufacturing ecosystem

(16) Promote the collaborative transformation of large, medium, and small enterprises. Support chain-leading enterprises in driving upstream and downstream enterprises to carry out "chain-style" transformation. In response to the transformation needs of small and medium-sized enterprises, research, develop, and promote specialized "small, fast, light, and precise" solutions to lower the threshold for transformation. Support enterprises in different industries and with different forms of ownership to accelerate the formation of intelligent transformation paths with their own distinctive features based on their existing foundations.

(17) Build a highland for innovation in intelligent manufacturing standards. Improve the construction of the intelligent manufacturing standards system, and prioritize the development and revision of standards in areas such as industrial agents, digital and intelligent upgrading of equipment, and the integration of intelligent scenarios with new technologies. Deepen international cooperation, promote the transformation of advanced international standards, and help local standards go global.

(18) Build a new-generation intelligent manufacturing public platform. Build an intelligent manufacturing supply-demand matching platform, integrate the city's scenario construction needs and service providers' product capabilities, and establish a closed-loop ecosystem of "technical research—scenario implementation—model replication." Build an intelligent manufacturing overseas empowerment platform to accelerate the going-global of high-quality products and high-level solutions from intelligent manufacturing service providers. Support high-quality enterprises in jointly building intelligent manufacturing pilot-testing platforms with upstream and downstream partners in the industrial chain, and carry out pilot-testing services such as data simulation, process improvement, sample trial production, testing and verification, and demonstration applications.

(19) Jointly create intelligent manufacturing leading zones. Deepen city-district coordination, and support each district in formulating "one district, one policy" plans for new-generation intelligent manufacturing focused on leading industries. Support the construction of a number of intelligent manufacturing leading zones, strengthen precise matching with high-quality enterprises and projects, promote the accelerated clustering of advantageous industries, and guide each district to take the lead and set an example in areas such as production organization paradigms, new manufacturing models, and industrial chain collaboration, forming a new-generation intelligent manufacturing development pattern featuring distinctive characteristics, multi-point support, and citywide coordination.

VI. Safeguard measures

Strengthen talent cultivation. Build a tiered cultivation system for interdisciplinary intelligent manufacturing talent, and implement cultivation programs such as frontier deployment engineers for intelligent manufacturing and continuous operation engineers for smart factories. Deepen the integration of industry and education, improve a training course system covering multi-level intelligent manufacturing talent, and increase training for industrial workers and skilled talent. Strengthen overall coordination. Strengthen departmental coordination, establish dedicated task force mechanisms among municipal departments, districts, and high-quality enterprises, establish a work system with clear responsibilities, orderly coordination, and effective supervision, strengthen task coordination, and carry out dynamic evaluation. Strengthen policy support. Accelerate the planning of major projects, actively undertake major national special projects such as the "Two Major" initiatives, and make coordinated and effective use of policies such as those promoting high-quality industrial development. Encourage each district to provide policy support in light of actual conditions.

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