Original Title: Notice Issued by the Shandong Provincial Department of Industry and Information Technology Regarding Supporting Documents for the "Shandong Province Manufacturing Digital Transformation Action Plan (2022–2025)"
I. Petrochemical Industry
(1) Main Objectives
By 2025, leading enterprises in the petrochemical industry will have achieved significant results in demonstrating and leading digital transformation. Digital solutions for the industry will be widely promoted and applied. The automation rate of key production facilities will reach over 98%, the stability rate will reach over 97%, the automatic collection rate of production data will reach over 90%, and the automatic collection rate of environmental protection data and the comprehensive digitization rate of key business processes will reach 100%. Production and operational costs will be reduced by 20%, and inventory turnover will increase by 20%.
(2) Implementation Path
1. Strengthen Lean Equipment Management. Enhance monitoring of equipment operating conditions, build digital twins for equipment, and monitor equipment performance in real time. Achieve integrated intelligent management of production command, process operations, and operational control through DCS and SIS systems.Utilize real-time equipment performance parameters to predict equipment operating conditions and potential failures, thereby enabling predictive maintenance; employ aerial surveillance equipment and thermal imaging cameras to effectively expand the scope and depth of monitoring for major regional risks, providing early warning support for hazardous chemical risk management.
2. Optimize process formulas and workflows. Conduct comprehensive simulation and modeling of process formulas and workflows to optimize raw material ratio parameters and plant optimization pathways, thereby achieving optimal refining and petrochemical production. Collect and analyze quality data throughout the entire oil refining process in real time, perform online dynamic analysis and predictive early warning for various quality indicators, and implement quality tracking and automatic control across the entire refining and petrochemical process. Strengthen data collection for key energy-consuming equipment and high-energy-consumption processing workflows, and reduce energy consumption by integrating big data and artificial intelligence algorithms.
3. Promote Collaborative Optimization of the Industrial Chain. Comprehensive application of next-generation information technologies will drive the implementation of smart manufacturing projects for integrated refining and petrochemical production, centered on the collaborative optimization of supply chains, industrial chains, and value chains. Real-time collection and analysis of supply chain operations will identify and improve inefficient resource allocation processes, thereby enhancing internal resource allocation efficiency. Using industrial internet platforms as connecting hubs, we will integrate upstream crude oil supply, midstream refining and petrochemical production, and downstream product sales to optimize resource allocation across the entire industrial chain.
4. Strengthen industry-wide demonstration of typical applications. Focusing on key application areas and critical stages of digital transformation—including business management, production operations, equipment control, safety and environmental protection, equipment management, quality control, online freight, and industrial chain synergy optimization—identify innovative demonstration models within the industry and establish a group of exemplary benchmarks for digital transformation. Encourage capable enterprises and institutions to form alliances or consortia to adopt market-oriented operational models for disseminating experience and product solutions to the industry, thereby promoting the widespread adoption of typical applications and new models across the entire sector.
5. Advance the development of a digital transformation management system. Continuously conduct assessments, diagnostics, and benchmarking guidance for industry digital transformation. In line with new trends in digital transformation and the development of the Industrial Internet, continuously improve the digital transformation maturity model, evaluation system, and assessment methods, and establish industry-specific digital transformation evaluation standards. Vigorously promote the development of an industry digital transformation standards system and develop a set of digital transformation standards that are urgently needed by the industry and have significant influence.
6. Conduct research and development on core digital transformation technologies. Strengthen research on the integrated application of new technologies—such as 5G, the Industrial Internet, artificial intelligence, big data, and digital twins—within the petrochemical industry, and encourage qualified enterprises to take the lead in piloting new technology innovations. In core business areas including business management, production operations, equipment health, safety and environmental protection, and supply chain collaboration, achieve breakthroughs in the application of key generic technologies to develop products and solutions that meet the industry’s major application needs, thereby providing technical support for high-quality digital transformation.
7. Build an industry transformation ecosystem. Focusing on the industry’s digital transformation needs, construct a business development roadmap for the deep integration of informatization and industrialization, establish a referenceable and replicable industry digital transformation system, and develop a functional application roadmap covering the entire enterprise process and all business operations. Establish and improve a talent development system for industry digital transformation, combining online and offline methods, theory and practice, and technology with business applications to cultivate a group of professionals capable of meeting the current demands of the industry’s digital transformation.
II. Steel Industry
(I) Main Objectives
Actively promote the integrated development of informatization, digitalization, and steel manufacturing technologies. Accelerate the construction of a steel manufacturing cloud platform and conduct pilot demonstrations of new smart manufacturing models, including process-oriented smart manufacturing, networked collaborative manufacturing, large-scale personalized customization, and remote operation and maintenance, to develop smart manufacturing solutions for the steel industry. By 2025, the penetration rate of digital workshops (smart factories) in the province’s steel industry will reach over 20%, the penetration rate of intelligent manufacturing in key production processes will exceed 50%, and the number of robots per 10,000 employees will reach over 250.
(2) Implementation Path
1. Promote the digitization of production processes. Utilize new technologies such as 5G and deterministic networks to build a high-speed network architecture with full coverage of business and production areas. By installing sensors, smart gateways, and other devices, accelerate the migration of key equipment and process stages to cloud platforms, establishing stable and efficient networks for material flow, energy flow, and information flow. Promote the integrated convergence of processes, leveraging artificial intelligence and big data analysis to enhance real-time monitoring, dynamic scheduling, and predictive early warning capabilities throughout the entire steel production process.Vigorously promote the application of intelligent detection equipment in key processes to facilitate the integration of environmental information and deep parameter sensing. In areas such as online continuous process measurement, online chemical composition analysis, and surface quality inspection, fully utilize machine vision and “image recognition + edge computing” technologies to enhance the data processing capabilities of edge devices.
2. Accelerate the intelligent management of equipment. Promote digital control systems such as PLCs and DCSs to expedite the implementation of digital control across the entire production process and ensure transparent data transmission between processes. Utilize 4C technologies—communication, control, and graphical display—to achieve decentralized control, centralized operation, hierarchical management, and flexible configuration.Intensify the promotion of centralized monitoring for general manned positions. For processes characterized by large workforces, high labor intensity, poor working environments, and numerous safety hazards, actively promote technologies such as unmanned operation and fully automated operation. Focusing on harsh environments—such as high noise, high dust, and high temperatures—as well as scenarios involving frequent repetitive operations, promote the application of intelligent industrial robots that integrate automatic identification, analysis, and operation to enhance capabilities in diversified sensing and adaptive control.
3. Building the "Brain" of the Steel Industry. Addressing the "black box" nature of steel manufacturing processes, integrate technologies such as sensing, computing, communication, and control to explore the establishment of a digital twin where elements of the physical and information spaces are mutually mapped, interact in real time, and collaborate efficiently.Utilizing smart inspection and deep sensing technologies, we will upgrade static models to dynamic real-time models. Based on augmented reality 3D visualization technology, we will construct a high-precision CPS system to create an “Industrial Brain” centered on “metallurgical mechanism models + mathematical models.” This will promote full-process digitization, visualization, and intelligentization, achieving self-sensing, self-decision-making, self-execution, and self-adaptation in production processes.
4. Deepen the implementation of collaborative manufacturing. Establish a data-driven quality control system for process operations, and enhance functions such as product quality rating, process monitoring, online judgment, and quality traceability and analysis. Implement refined equipment management and build an equipment maintenance system capable of precise online condition monitoring, operational stability monitoring, safety prediction and early warning, predictive maintenance, and full lifecycle management.Optimize energy management by strengthening online energy monitoring, dynamic scheduling, and predictive early warning. Based on comprehensive energy data and utilizing big data analytics, advance energy balance optimization. Focus on safety production prediction and early warning, graded control of safety risks, emergency management, and online monitoring of major hazard sources to build a safety supervision platform that integrates environmental data collection, archiving, reporting, analysis, and predictive assessment.
III. Non-ferrous Metals Industry
(1) Main Objectives
Promote the digital aggregation, networked sharing, and platform-based collaboration of manufacturing resources such as equipment, materials, and energy. By 2025, significant progress will be made in the digital transformation of the non-ferrous metal smelting and rolling processing industry, and notable breakthroughs will be achieved in key generic technologies for smart manufacturing.the comprehensive digitization rate of key production processes in enterprises above a certain scale will reach 90%, and the digitization rate of production equipment will reach 80%. Two cloud platforms for the non-ferrous metal smelting and rolling processing industry will be established, and a range of application scenarios for next-generation technologies—including big data, cloud computing, the Internet of Things (IoT), blockchain, virtual reality, and the Industrial Internet—will be developed.
(2) Implementation Path
1. Accelerate the construction of information infrastructure. Encourage enterprises to utilize new network technologies such as 5G and Industrial PON (Passive Optical Network) to accelerate the upgrade of existing networks toward high-speed, low-power, and high-reliability standards, thereby building a ubiquitous and integrated industrial digital network. Establish a number of demonstration benchmarks for large-scale promotion across the province. Support leading enterprises in the industry to collaborate with “cross-industry and cross-domain” platforms to build an industrial internet platform for the non-ferrous metals sector.Encourage key enterprises to establish a number of secondary nodes for identifier resolution to enhance the identification capabilities of production lines, equipment, and products, thereby enabling full lifecycle management—including manufacturing, resource management, and market decision-making—across upstream and downstream enterprises.
2. Implement digital transformation of production management. Support enterprises in establishing end-to-end digital MES (Manufacturing Execution Systems), creating digital twins that enable real-time synchronization of data sources across multiple dimensions and environments, and building smart manufacturing cells, smart production lines, and digital workshops.Enhance ERP (Enterprise Resource Planning) functionality, deepen the digital integration of core business operations such as production, supply, and sales, and promote transparent, visual, and digital management of production data, quality data, and anomaly information. Support key enterprises in building an integrated “PLM+MES+ERP” enterprise operations platform, developing models for order management, supply chain management, and financial management, and establishing an efficient supply chain collaboration system.
3. Promote joint R&D of key technologies.Leveraging key enterprises in the industry, establish 1–2 national-level innovation platforms for the non-ferrous metal smelting and rolling processing sector. Focusing on the development needs of smart mines, smart factories, and digital workshops, strengthen exchanges and cooperation with research institutes, university think tanks, and digital transformation service providers to build an ecosystem for collaborative technological innovation. Promote research into key generic technologies as well as the R&D of smart components, equipment, and systems; accelerate the formulation of industry smart manufacturing standards; and enhance the development and application of advanced mechanistic models.
4. Develop comprehensive industry solutions. Actively explore the deep integration of the Industrial Internet with the non-ferrous metal smelting and rolling industry, promote the migration of key enterprises and equipment to cloud-based platforms, and achieve the interconnection of manufacturing resources and capabilities.Tailored to the characteristics of specific non-ferrous metal sub-sectors, focus on key stages such as mining and smelting, processing into finished products, logistics and warehousing, and online inspection. Develop digital system solutions featuring intelligent sensing, automated execution, deep learning, intelligent decision-making, and cryptographic protection. Research and develop industry-specific mobile applications to drive the transformation of production methods toward automation, intelligence, and unmanned operations.
5. Strengthen the application and promotion of information technology. Promote the deep integration of technologies such as AI, machine vision, and knowledge graphs with the non-ferrous metal smelting and rolling industry. Encourage key enterprises to develop CNC systems and guide equipment manufacturers to open data interfaces to achieve comprehensive data collection and integration, thereby accelerating the application of AI technology across all links of the industrial chain and throughout the entire product lifecycle.Carry out digital upgrades of key equipment by installing sensors, communication modules, and controllers, and conduct precise monitoring, production optimization, and remote diagnostics based on industrial internet platforms. Vigorously promote the innovative application of industrial big data, establish real-time databases for equipment status, and innovate data-driven management and decision-making models.
IV. Building Materials Industry
(1) Main Objectives
By 2025, the digital transformation of the province’s building materials industry will have made significant progress, with notable breakthroughs in the R&D of key generic technologies. Leading enterprises in the three key sectors—cement manufacturing, flat glass, and architectural ceramics—will achieve significant results in serving as digital demonstration leaders, driving a substantial improvement in the industry’s overall digitalization level. The CNC rate for key production processes at building materials manufacturers will reach over 90%, and the digitalization rate of production equipment will reach approximately 80%;Cultivate 100 exemplary projects that have achieved outstanding results in R&D and design, manufacturing, supply chain management, e-commerce, and equipment operation and maintenance; create 50 industrial apps for the building materials industry; and establish 10 benchmark enterprises for digital transformation.
(2) Implementation Pathways
1. Build industry digital platforms. Support key enterprises in leading the establishment of provincial-level public service platforms for the building materials industry to promote division of labor, collaboration, and shared development across the industrial chain. Guide the formation of a provincial digital collaborative innovation center for the cement industry to foster deep integration between the Industrial Internet and the province’s cement industry.Support leading enterprises in the industry to build digital industrial chain development platforms and technology R&D centers. Implement a series of projects to upgrade and enhance intelligent digital production lines with a capacity of 4,000 tons per day or more, and promote the construction of a world-class, high-end intelligent cement clinker production line with a daily output of 10,000 tons.
2. Develop systematic solutions. Tailored to the characteristics of specific building materials sub-sectors, focus on key processes such as mining, kiln control, logistics and warehousing, and online inspection to develop and promote the application of solutions. In the cement industry, prioritize the development of solutions for digital planning and design, smart factory construction, automated ore mining, beneficiation, and blending, kiln optimization control, equipment diagnostics and maintenance, intelligent quality control, energy and water consumption management, and coordinated solid waste disposal.In the glass industry, the focus is on developing solutions for raw material beneficiation and batching; intelligent thermal control of the melting furnace, tin bath, and annealing furnace; cold-end optimization control; online defect detection; and automatic cutting and sorting. In the architectural ceramics industry, the focus is on developing integrated system solutions for raw material standard data, press control and management, intelligent high-pressure slip casting, green body drying control, kiln optimization control, product glazing, grinding, and polishing, as well as automatic inspection and sorting.
3. Deepen the integration and application of digital technologies. Encourage enterprises to apply IoT technologies to achieve intelligent sensing, identification, positioning, tracking, and management; migrate infrastructure, business systems, and equipment products to the cloud; cultivate industrial apps; and build an industrial internet platform for the building materials industry. Support enterprises in utilizing blockchain technology to enable product transactions, information traceability, and quality management with upstream and downstream supply chains, ensuring data security and gradually deepening its application.Promote the application of advanced algorithms, machine learning, and smart chips in the building materials industry across areas such as smart production, smart decision-making, smart logistics, smart monitoring, and smart traceability. Utilize computational modeling, real-time sensing, virtual reality, and simulation technologies to create virtual representations of building materials factories, thereby facilitating full-cycle optimization management—including the design, installation, and operation of complete production facilities—and achieving factory visualization, predictability, and maintainability.
4. Advance digitization in key processes. Focus on critical production and operational stages in the building materials industry to accelerate the adoption of advanced technical solutions such as kiln optimization control, intelligent warehousing and logistics, equipment inspection and maintenance, and online monitoring and testing, and cultivate a number of exemplary projects.Accelerate the implementation of "automation replacing manual labor" in physically demanding and hazardous positions—such as material handling and palletizing, feeding and loading, polishing and glazing, painting and sanding, and high-temperature kilns—as well as in high-precision roles involving image recognition, cutting and sorting, pressure molding, and sampling and testing.Guide enterprises to increase investment in smart manufacturing, accelerate the application of smart sensors, optimized smart control systems, and fault diagnosis and maintenance in key processes and core products, and strengthen the foundation of intelligent and digital hardware and software.
5. Cultivate a group of industry benchmarks. Leverage the exemplary and leading role of model enterprises in digital transformation, and thoroughly implement the “Digital Specialists in Enterprises” initiative. Strive to complete the digital and intelligent transformation of all clinker production enterprises and more than 100 cement grinding enterprises across the province, cultivate a group of digital benchmark enterprises, and establish a number of smart factories in the building materials industry to effectively improve product quality, operational efficiency, equipment management, and safety and environmental protection standards.Organize key enterprises to implement the integration of informatization and industrialization management system standards, and encourage eligible enterprises to apply for certification. Guide outstanding provincial enterprises to actively participate in the research and formulation of standards and regulations for smart factories and digital mines, thereby continuously elevating the standardization level of the building materials industry.
V. Automotive Industry
(1) Main Objectives
We will vigorously advance the intelligent production, precision marketing, data-driven operations, and smart management of the automotive industry, fostering new business formats, models, and growth drivers to promote its digital transformation. By 2025, the industry-wide rate of CNC application in key production processes will reach 60%, the adoption rate of digital R&D and design tools will reach 80%, 100 digital workshops will be certified, and a provincial automotive industrial chain with an output value of 300 billion yuan will be established, propelling the automotive industry into the era of digitalization and intelligent manufacturing.
(2) Implementation Pathways
1. Expand the scope of robotics applications. Support enterprises in undertaking intelligent project development, identify application scenarios in automotive and parts manufacturing, and continue to implement “robot substitution” initiatives in standardized repetitive operations, painting and assembly tasks, laser welding, precision assembly, non-destructive testing, and other critical processes and positions. Prioritize the promotion and application of industrial robots for material handling, welding, assembly, painting, and palletizing.
2. Enhance flexible production capabilities. Encourage vehicle manufacturers to adopt technologies and equipment such as multi-size adjustable fixtures and molds, diverse feeding systems, rapid cleaning devices for paint shops, and multi-model chassis transport systems. Establish flexible final assembly lines, ultra-high-flexibility painting lines, and flexible machining lines.Carry out flexible production line retrofits to enable simultaneous batch production and mixed-line production of multiple vehicle models and configurations, and continuously expand personalized customization capabilities. Support vehicle and parts manufacturers in promoting computer-aided design (CAD) and computer-aided manufacturing (CAM), adopting virtual prototyping technology to achieve virtual evaluation and enhance the intelligence of product R&D.
3. Promote the digital transformation of production lines. Support the digital transformation of special-purpose vehicle and automotive parts industrial clusters in Jinan, Qingdao, Jining, Weifang, and other regions, and promote the construction of digital workshops. Encourage special-purpose vehicle manufacturers to introduce technologies such as laser cutting, robotic welding, and electrophoretic painting, and actively carry out digital demonstration and promotion.Encourage parts manufacturers to enhance digital capabilities in the production of brake pads, filters, structural components, and other areas, and conduct digital upgrade demonstrations in key automotive parts sectors such as engines, automotive molds, aluminum alloy wheels, cylinder blocks and heads, and crash bars. Adopt Total Quality Management (TQM) and Quality Traceability Systems (QTS) to collect quality data and trace the root causes of issues, thereby improving the digitalization and intelligence of quality control.
4. Deepen the development of the Industrial Internet. Encourage enterprises to accelerate the construction of corporate intranets, establish secondary nodes for identifier resolution, increase equipment connectivity rates, and expedite the comprehensive integration and cloud migration of various application systems. This will enable the collection, analysis, and cloud-based aggregation of industrial data, promote the organic integration of data flows and business processes within key automotive industrial clusters’ supply chains, and achieve seamless material handover and full lifecycle traceability.Actively promote collaboration between enterprises and industrial internet companies, cultivate industrial internet platforms for the automotive sector, and facilitate the optimal allocation of manufacturing resources. This will enable collaborative production among manufacturers of complete vehicles, powertrain systems, and high-performance batteries, while driving the coordinated and clustered development of enterprises across the entire industrial chain.
5. Accelerate enterprise migration to the cloud and platforms. Promote the migration of equipment, data, and infrastructure to the cloud for small and medium-sized automotive parts manufacturers, effectively reducing the costs of digital transformation, and gradually forming a new ecosystem driven by digitalization, networked collaboration, and shared development.Encourage vehicle manufacturers to establish private clouds and utilize public clouds, deeply explore cloud application scenarios such as real-time data from manufacturing lines and synchronous updates of cloud-based data, and explore distributed “cloud computing” models to meet application needs such as simulation and evaluation, digital twins, process simulation, and virtual factories. Encourage enterprises to apply digital twin technology to achieve digitalization of process flows, standardization of production and manufacturing, and intelligent operation and maintenance of production equipment.
6. Promote innovative applications of vehicle-to-everything (V2X) technology. Support key provincial enterprises in collaborating with leading internet and artificial intelligence companies to advance the R&D and industrialization of electronic products for applications such as autonomous driving, intelligent management and control systems, smart cockpits, driving safety, and V2X information services. Accelerate the implementation of the Shandong Expressway vehicle-road coordination demonstration project and the two national-level intelligent connected vehicle and smart transportation demonstration projects in Jinan and Heze.Establish an Innovation Center for Intelligent Connected Vehicles to advance the R&D of cutting-edge key technologies such as in-vehicle optical systems, in-vehicle radar systems, and high-precision Beidou positioning, and to develop intelligent connected vehicles and related information services.
VI. Construction Machinery Industry
(1) Main Objectives
By 2025, the digital transformation of the construction machinery industry will have achieved significant results, forming a sound development pattern characterized by tiered growth among large, medium, and small enterprises and the coordinated advancement of “digitalization, networked collaboration, and intelligent upgrading.” This will propel the manufacturing and service capabilities of the construction machinery industry toward the mid-to-high end of the value chain. A total of 200 digital workshops (smart factories) will be established, with operational costs for smart manufacturing demonstration projects reduced by 20%, product development cycles shortened by 20%, and production efficiency increased by more than 20%.
(2) Implementation Path
1. Optimize the construction of digital infrastructure. Accelerate the deployment of 5G networks to build high-quality networks capable of meeting the demands of device interconnection and remote interaction applications in industrial environments. Promote the development of deterministic networks and expand applications such as “deterministic networks + remote control” and “deterministic networks + computing power sharing.” Encourage enterprises to collaborate with digital transformation service providers to establish enterprise-level and industry-level industrial internet platforms, thereby fostering coordinated development among enterprises within the same organization and across the entire industrial chain.
2. Strengthen technological support for industry digitalization. Focus on overcoming key technical challenges in data collection, transmission, and control across three key areas: construction sites, equipment, and client terminals. Enhance the efficient collection and aggregation of data regarding equipment operational status, customer needs, and feedback. Improve capabilities for constructing digital models for business operations management, manufacturing, and remote equipment maintenance. Strengthen algorithm-driven data processing and mining capabilities, and refine data management and service mechanisms to provide reliable technical support for digital transformation.
3. Enhance the capacity of digital platforms. Strengthen the development of digital platforms, improve hardware and software capabilities, and increase openness. Support the joint construction of digital innovation and operational platforms by industry, academia, research institutions, and end-users to drive industrial chain upgrading through data chains and continuously enhance collaborative innovation capabilities across the industrial chain. Using digital platforms as a vehicle, focus on areas such as digital design, digital manufacturing, remote operation and maintenance, and data mining and application to attract and cultivate a cohort of digital manufacturing engineering and technical talent, thereby propelling the digital transformation, upgrading, and high-quality development of the construction machinery industry.
4. Enhance the Level of Digital Empowerment. Encourage in-depth cooperation among intelligent equipment manufacturers, software vendors, and construction machinery enterprises. Apply systems such as CAD, CAM, MES, ERP, and CRM to develop a range of intelligent equipment, including industrial robots, intelligent sensing and control systems, and intelligent inspection and assembly systems. Achieve digital applications across R&D, production, operations, and service processes within construction machinery enterprises to enhance R&D and manufacturing capabilities as well as lean management standards.
5. Implement the New Product Development Initiative. Accelerate the integration of new technologies—such as embedded chips, sensors, 5G, big data, and artificial intelligence—with traditional construction machinery products to develop networked and intelligent new products.Focus on achieving innovative breakthroughs in areas such as complete construction machinery manufacturing, high-horsepower engines, high-end hydraulic components, and basic components. Develop high-end intelligent construction machinery, large-scale mining machinery, new energy construction machinery, and unmanned intelligent machinery. Cultivate approximately 20 major technological equipment and key component products (including first-of-their-kind sets) annually, gradually achieving self-reliance in major technological equipment and driving the development of supporting products.
6. Promote Demonstrations of Intelligent Upgrades. Focusing on key areas such as the automation of critical processes, the replacement of key positions with robots, intelligent optimization and control of production processes, and intelligent supply chain management, support the creation of digital demonstration workshops for discrete manufacturing. Centered on “interconnected equipment, shared data, interoperable systems, and integrated business models,” support leading enterprises in partnering with smart manufacturing system integrators to build demonstration factories that cover the entire production process, all aspects of management, and the full product lifecycle.Guide key construction machinery enterprises to transition from manufacturing to a “manufacturing + services” model, develop and deploy industrial apps for operational monitoring and analysis, and provide intelligent operation and maintenance solutions. Based on supply chain optimization needs, develop cloud-based application services for centralized procurement, supplier management, flexible supply chains, intelligent warehousing, and smart logistics.
VII. Rail Transit Equipment Manufacturing
(1) Main Objectives
By 2025, significant progress will have been made in the digital transformation of the rail transit equipment manufacturing industry. Next-generation information technologies will be deeply integrated with the sector, establishing a new development paradigm characterized by digitalized R&D and design, flexible manufacturing, integrated supply chain management, and intelligent vehicle operation and maintenance. Leading enterprises will generally have established digital workshops (factories), with the rate of CNC-equipped production equipment reaching 70%,the adoption rate of digital R&D and design tools will reach 90%, the CNC rate for key processes will exceed 60%, and the efficiency of industrial resource allocation will be significantly improved.
(II) Implementation Pathways
1. Strengthen the application of digital twin technology. Support key enterprises in building production system models that integrate manufacturing processes based on digital twin technology, forming a digital twin-based manufacturing system. Synchronize digital models with physical equipment in real time to continuously drive iterative optimization in product design, manufacturing, and services, achieving end-to-end digital integration from R&D to processes and from production to services.
2. Prioritize the digital transformation of R&D and design. Promote the shift of R&D and design from experimental verification to platform-based simulation. Utilize platform-based simulation to inspect and analyze components, thereby improving resource utilization and the efficiency of R&D simulation verification. Build virtual simulation environments based on these platforms, establish simulation models, and conduct virtual simulations and iterative optimization through operating condition settings and parameter inputs to shorten R&D cycles and reduce R&D costs.
3. Enhance the digitalization of production processes.Support the promotion and application of key smart manufacturing technologies, equipment, and core supporting software in the rail transit equipment manufacturing sector. Utilize big data systems and cloud service technologies to promote the digital and intelligent development of all stages—including R&D design, production manufacturing, testing and inspection, and operational management. Support eligible enterprises in building digital and smart factories (workshops) and establishing smart manufacturing production lines to achieve high levels of human-machine collaboration. Gradually expand the scope of smart manufacturing applications to drive the industry’s advancement in digitalization and intelligent capabilities.
4. Promote the development of industry-wide digital platforms.Encourage leading enterprises in the industry chain to build industrial internet platforms, collect train status data in real time, establish real-time status sensing, monitoring, and early warning systems, expand remote operation and maintenance services for rail transit equipment, and explore new models for train status monitoring and rapid fault alerts. Relying on big data cloud platforms to integrate train-related data, develop intelligent analysis systems for rail transit vehicle manufacturing and vehicle operation and maintenance, and provide technical support for the design, manufacturing, operation, maintenance, repair, and service life of rail transit systems.
5. Accelerate the intelligent transformation of products in key areas. Integrate technical resources from leading enterprises, research institutes, and universities, focusing on core equipment, system software, critical materials, and basic components. Relying on the National High-Speed Train Technology Innovation Center, achieve breakthroughs in a number of key core technologies to create a new generation of intelligent rail transit equipment characterized by the convergence of information and physical systems. This will enhance the intelligence level of complete vehicle products and achieve intelligent monitoring, decision-making, and user experience.
6. Deepen the promotion and application across the entire industrial chain. Taking the full lifecycle of rail transit equipment as the main focus, we will utilize standardized and regulated processes along with advanced IoT front-end sensing technologies. By leveraging industrial internet platforms to collect data from supply chains, manufacturing chains, and service chains, we will promote the optimization of industry resource allocation and the enhancement of service capabilities. We encourage small and medium-sized enterprises to actively join the ranks of digital and intelligent transformation, achieving widespread digitalization, networked collaboration, and intelligent upgrades in key areas such as design, manufacturing, and management.
VIII. Shipbuilding Industry
(I) Main Objectives
By 2025, the digitalization level of the shipbuilding industry will be significantly enhanced. A number of key technologies and smart manufacturing equipment will be developed, a set of smart manufacturing standards and platforms will be established, and a number of smart manufacturing units, smart production lines, and smart workshops will be built. Full digital coverage will be achieved across the entire process of design, production, and operation, forming a seamless connection, parallel manufacturing, and coordinated development between final assembly enterprises and supporting enterprises.The rate of CNC equipment adoption among key enterprises in the industry will reach 50%, the penetration rate of digital R&D and design tools will reach 80%, the rate of CNC adoption in key processes will reach 60%, and the proportion of enterprises with comprehensive digitalization across key business processes will reach 60%.
(2) Implementation Path
1. Strengthen the application of next-generation information technologies. Accelerate the digital application of technologies such as big data, virtual simulation, system collaboration, and artificial intelligence in the shipbuilding industry; expand the scope of data usage within the industrial internet; and leverage platforms to conduct simulation testing, collaborative design, process optimization, visual inspection, and intelligent control and management, thereby further reducing prototyping costs, improving production efficiency, and ensuring product quality.
2. Promote the establishment of an industry software support system. Increase R&D investment in core technologies for intelligent shipbuilding, including overall technology, process design, intelligent control and management, and intelligent decision-making. Leverage national major special projects such as the High-Tech Ship Research Program. Focusing on the intelligent development of the shipbuilding industry and aiming for the integration of shipbuilding software, integrate superior resources from both within and outside the industry to accelerate breakthroughs in core technologies such as 3D geometric kernels, basic solvers,CAX integrated open platforms, and build a shipbuilding industrial software support system.
3. Launch a Digital Twin Innovation Initiative. Support shipbuilding enterprises in utilizing industrial cloud platforms to aggregate various industrial data from ships and shipyards, deploy simulation modules such as CAE and CAD, simulate manufacturing processes including component machining, welding, and assembly, and conduct collision tests on ship models in the digital space to reduce prototype development costs and shorten product R&D cycles.Establish an online inspection platform for shipowners and classification societies. Based on movable and rotatable 3D digital twin models, this platform will visually present ship inspection data, enhance the real-time nature of inspections, and ensure product quality.
4. Establish a digital system for smart manufacturing. Establish a CPS-based digital system for smart manufacturing and deploy intelligent robots in key production stages such as material feeding, cutting, welding, and transportation. Develop multi-level, multi-granularity positioning systems based on Beidou and RFID to promote ubiquitous connectivity of core production elements throughout the entire shipbuilding process. In core shipbuilding processes such as cutting and welding, establish a workshop-level edge intelligence control network.Construct logical models of production workstations, production lines, and workshops; build a digital system for monitoring the status of core production elements and controlling operational conditions; and conduct dynamic analysis, decision-making, and scheduling of production processes based on real-time status data.
5. Build a Supply Chain Collaborative Innovation Ecosystem.Promote cooperation among manufacturers with strong R&D and production capabilities to implement digital lean management for shipbuilding materials, suppliers, material distribution, and financial leasing. This will ensure a balanced and orderly supply chain, effectively improving logistics turnover efficiency. Support enterprises in building specialized technological innovation platforms, pooling resources from top domestic manufacturers and think tanks to establish a close-knit alliance ecosystem guided by the government, involving enterprises across the entire industrial chain, and strongly supported by research institutions, thereby continuously enhancing the autonomy and controllability of the industrial and supply chains.
6. Expand and Deepen Industry-Wide Digitalization. Guide shipbuilding enterprises to play a leading role, strengthen cooperation and exchange with major industrial internet platforms, actively address pain points and challenges in the intelligent shipbuilding process, and advance the digitalization, networking, and intelligent transformation of the entire lifecycle of ship and offshore engineering products—including design, construction, management, and services.With digital transformation as the primary focus for strengthening management, reducing costs, and improving efficiency in the shipbuilding industry, vigorously promote the application of digital technologies. Establish a number of smart units, smart production lines, and smart workshops that meet advanced domestic standards, achieving a reduction of more than 20% in man-hours per gross ton.
IX. Food Industry
(1) Main Objectives
By 2025, the food industry across the province will have made significant progress in digital transformation, achieved notable breakthroughs in the research and development of key generic technologies, and seen a marked improvement in the application of the integration of informatization and industrialization. New technologies, products, models, and business formats will continue to emerge, and the overall digitalization level of the industry will be substantially enhanced.Significant results will be achieved in the digital demonstration and leadership of key enterprises within the industry, as well as in the promotion and application of digital solutions. Over the next 3–5 years, a number of industrial internet platforms will be established in key food sub-sectors such as baijiu, beer, wine, and edible vegetable oil. Two hundred benchmark enterprises for industrial internet platform applications in the food industry will be cultivated, and 100 benchmark projects for digital transformation will be announced and promoted.
(II) Implementation Pathways
1. Promote comprehensive technological upgrading across the industry. Key enterprises in the food sector are encouraged to leverage digital empowerment to accelerate technological upgrades in areas such as novel non-thermal processing, new sterilization methods, high-efficiency separation, energy-saving drying, clean production, and comprehensive utilization. This will increase the proportion of deep processing in key sectors including grain and oil, meat, eggs, and dairy, fruits and vegetables, and marine and aquatic products.Focusing on key sectors such as food processing and manufacturing, machinery and equipment, quality and safety, cold-chain logistics, and nutrition and health, conduct full-chain technological research ranging from foundational and cutting-edge technologies to major key generic technologies and application demonstrations to promote the healthy and high-quality development of the food industry. By the end of the 14th Five-Year Plan period, the comprehensive deep processing conversion rate of the food industry will reach over 75%.
2. Promote the deep integration of informatization and industrialization. Accelerate the application of next-generation information technologies—such as cloud computing, big data, and the Internet of Things—in food R&D, design, production, manufacturing, distribution, and consumption.Intensify systematic R&D in key stages of food production and processing, guide provincial food enterprises to increase investment in smart manufacturing, cultivate a group of benchmark enterprises for industrial internet platform applications in the food industry, and promote a batch of benchmark projects for digital transformation. Develop personalized customization and flexible manufacturing, encourage key enterprises in the food industry to build digital workshops, carry out pilot demonstrations for smart factory construction, and enhance the level of intelligence. Support key food enterprises in expanding the coverage of traceability systems to achieve full traceability of food “from farm to table.”
3. Foster the Development of New Business Models and Formats. Promote the in-depth application of the Industrial Internet and artificial intelligence in the food sector, and promote new models such as central kitchens and direct farm-to-retail supply chains that implement “unified centralized procurement, unified production processes, unified quality standards, unified sales prices, and unified distribution methods.” Guide the food industry to utilize “Internet Plus” technologies to deeply integrate with sectors such as leisure, tourism, culture, education, science popularization, and health and elderly care, and develop new business formats such as industrial tourism, manufacturing process experiences, and product design and creativity.Innovate integrated application models for e-commerce and the food industry; support the establishment of industry-specific vertical e-commerce platforms operating under diverse models; and promote the integration of online transactions, electronic payments, and online-offline integration. Showcase 10 exemplary cases of new business formats and models annually.
4. Strengthen blockchain applications in specialized sectors. Accelerate the adoption of blockchain technology in sectors such as alcoholic beverages, grain and oil processing, and meat product processing. Build industry-specific blockchain public service platforms. Through cloud migration, data utilization, and intelligent applications, connect upstream and downstream segments of the industrial chain, manufacturing facilities, and consumers. Promote the integration and enhancement of service elements within the food industry chain, providing services such as product visualization, supply chain management, digital marketing, big data analysis, and social evaluation of quality and brand reputation.to build a new production, manufacturing, and service system featuring deep connectivity across the entire industrial chain, achieving “precision decoding” in R&D, “precision execution” in smart manufacturing, and “precision navigation” in sales.
5. Create Digital Development Clusters in the Food Industry. Focusing on leading food processing sectors such as marine foods, livestock and poultry meat products, edible vegetable oils, alcoholic beverages, starch processing and functional starch sugars, fruit and vegetable processing, snack foods, and health-functional foods, we will build digital development clusters based on leading enterprises and supported by counties, towns, and industrial parks with distinctive food industry strengths. These clusters will foster resource sharing and open collaboration.Support leading enterprises within the industrial cluster in collaborating with universities and research institutions to tackle key challenges, accelerating breakthroughs in common core technologies such as production processes, quality control, packaging design, brand marketing, and ecological sustainability. Establish a low-cost, convenient, and open digital innovation service platform for small, medium, and micro food enterprises, fostering a new digital ecosystem where large, medium, and small enterprises develop in tandem and support one another.
X. Textile and Apparel Industry
(I) Main Objectives
Accelerate the integrated innovation and development of next-generation information technology with the textile and apparel industry, driving the sector toward green, low-carbon, digital, and intelligent transformation. By 2025, significant progress will be made in the digital transformation of the textile and apparel industry, with a new digital development framework largely established—supported by big data and industry platforms, and oriented toward flexible production and personalized customization. Cultivate 2–3 industrial internet platforms with significant influence in the national industry, and achieve a 75% digitalization rate of production equipment among key enterprises.
(2) Implementation Pathways
1. Enhance Digital Management Capabilities. In sectors such as spinning, weaving, and dyeing, establish a group of green and smart factories; guide enterprises to vigorously implement smart technological upgrades, gradually achieving intelligent production processes, smart control systems, and informatized online monitoring. Encourage enterprises to comprehensively apply next-generation information technologies throughout the entire production management process, build an enterprise intranet connecting people with machines, machines with materials, and machines with machines, strengthen real-time analysis and monitoring of orders, equipment, and materials, and achieve intelligent production scheduling and supply chain collaboration.
2. Enhance the Intelligence Level of Equipment. Tailored to the characteristics of textile and apparel enterprises, focus on key processes such as new fabric design, garment comfort testing, 3D scanning and measurement, and high-end printing to accelerate the adoption of digital machinery and equipment, thereby elevating the intelligence level of apparel production.Encourage the construction of new smart production workshops equipped with intelligent machinery such as high-speed textile machinery, dyeing and finishing equipment, hanging flexible assembly lines, digital printing systems, and vision-based quality inspection systems to achieve intelligent control of production processes. For existing traditional workshop production lines, support enterprises in implementing flexible upgrades using emerging technologies such as industrial big data and artificial intelligence to enhance personalized customization capabilities.
3. Establish a networked marketing model. Integrate market and channel resources, leveraging the textile and apparel industry’s proximity to end-user markets. Encourage enterprises to utilize online shopping platforms and live-streaming sales platforms to create new sales scenarios such as live-stream e-commerce and social e-commerce, forming a closed-loop ecosystem encompassing e-commerce traffic generation, order conversion, and online services. Actively attract renowned domestic and international marketing planning and brand promotion agencies to establish operations within industry parks (platforms), guiding enterprises to optimize marketing strategies and increase the proportion of e-commerce sales.
4. Cultivate Model Enterprises for Transformation. Targeting the production and process characteristics of specific segments, focus on launching digital transformation demonstration initiatives in key areas such as: - Information-based cotton blending management in the cotton spinning and weaving stages; - Online monitoring of fabric printing and dyeing process parameters in the printing and dyeing stage; - Digital body scanning, automated sewing equipment, and hanging systems in the apparel design and manufacturing stages; - AI-powered body measurement and customer recognition in the digital sales stage.Accelerate the cultivation of a group of exemplary benchmarks in intelligent manufacturing, personalized customization, and platform-based applications to demonstrate and drive industry enterprises toward a transition to large-scale, personalized online customization and flexible production characterized by small batches, multiple varieties, and fast turnaround times.
5. Build an integrated and shared ecosystem. Through the demonstration and leadership of leading enterprises, technical support from service providers, and innovation-driven guidance from research institutions, we will drive small and medium-sized enterprises (SMEs) to implement digital transformation, creating a development ecosystem where large, medium, and small enterprises share intelligence, production capacity, and business models.Encourage textile and apparel enterprises to open up cloud-based innovation and design resources, and promote the flexible exchange and shared use of development tools, design components, process parameters, professional knowledge, and new technologies. Support textile and apparel enterprises with successful digital transformation experience and technical capabilities to transition into digital transformation solution providers and full-process digital platform enterprises.
XI. Electronic Information Manufacturing Industry
(1) Main Objectives
Comprehensively enhance the digitalization level of the electronics and information manufacturing sector across equipment management, R&D and production, product quality control, and supply chain collaboration. Build a group of influential industrial internet platforms for the electronics and information manufacturing sector. By 2025, achieve breakthrough progress in the digital transformation of the electronics and information manufacturing sector, with 75% of manufacturing enterprises above a certain scale achieving full digitalization of key business processes, and the digitalization rate of production equipment in key enterprises reaching 58%.
(2) Implementation Path
1. Promote the interconnection and interoperability of data resources. Support enterprises in carrying out networked upgrades of industrial equipment, promote “open interfaces and machine connectivity,” and expand network coverage and the number of connected terminals. Guide enterprises to establish EAP (Equipment Automation System) and MES to optimize the utilization of production data. Support enterprises in installing smart terminals with edge computing capabilities to collect data from R&D, production, sales, and other processes.Strengthen edge data analysis capabilities by deploying cloud-based machine learning and deep learning algorithms directly on production equipment to enable automatic adjustment and optimization. Establish an efficient system for integrating, parsing, and managing massive volumes of heterogeneous data—including relational, temporal, and document-based data—generated during enterprise operations, thereby facilitating cross-domain data circulation.
2. Build industry-specific industrial internet platforms. Promote the accumulation and consolidation of knowledge and experience from the electronic information manufacturing sector on these platforms, accelerating the conversion of industrial knowledge—such as foundational processes, control methods, and operational mechanisms—into software and models. Focusing on areas such as equipment management, R&D design, product quality testing, and supply chain collaboration, develop mechanistic models and construct knowledge graphs to enable tag-based management, intelligent search, and precise retrieval.Collect operational, environmental, and process data from production equipment via the platform to analyze and predict trends in key component performance, product lifespan, and potential risks, enabling proactive predictive maintenance. Utilize big data analytics to mine and analyze equipment work logs, historical failures, operational trajectories, and real-time locations, achieving precise localization of equipment failures.
3. Optimize R&D and production management processes. Focusing on parameters such as processes, functionality, quality, testing, and operating environments, we will construct digital twin models of products to explore “zero-cost trial-and-error” R&D.Conduct modeling tests and intelligent scheduling for production planning, order management, quality management, material management, and equipment management to shorten product production cycles. Utilize machine vision and artificial intelligence technologies, combined with product quality analysis models, to promptly identify potential quality issues and eliminate loopholes in quality management processes. Based on the Industrial Internet of Things (IIoT) platform, integrate data across raw material supply, component manufacturing, parts production, assembly and processing, integrated sales, and operations and maintenance to achieve full-lifecycle product quality tracking and enhance the precision of quality control.
4. Optimize Supply Chain Collaborative Resource Allocation. Collect real-time data on in-house equipment, tools, materials, and labor; track on-site material consumption in real time; and perform precise order fulfillment based on inventory status to achieve dynamic optimization of production and inventory. Using the Industrial Internet of Things (IIoT) platform as a connectivity hub, collect real-time operational data—including production scheduling, manufacturing, inventory, quality, and logistics—from upstream and downstream supply chain partners. By integrating this data with supply chain collaboration models, optimize resource allocation across the entire supply chain to achieve dynamic and precise supply chain coordination.Addressing information bottlenecks and supply-demand mismatches across the upstream and downstream segments of the electronics industry’s supply chain, we develop supply chain collaboration solutions to improve the overall efficiency of resource allocation.
5. Enhance digital service capabilities. Develop solutions for equipment condition monitoring, fault diagnosis, and predictive maintenance to improve intelligent equipment management. Promote the digitization of product R&D, production scheduling, quality inspection, and lean management to further optimize enterprise production management and enhance product quality precision.Leverage the roles of government departments, industry associations, and industrial alliances to broaden channels for technology R&D, investment and financing, and talent cultivation and recruitment in the electronics and information manufacturing sector. Encourage suppliers to fully identify enterprises’ digital transformation needs, gather ecosystem partners, and engage in cooperation on technology, marketing, operations, and services. Support research institutions, universities, and enterprises in conducting collaborative technological innovation, experimental validation, and industrialization promotion among industry, academia, research, and application sectors.
