Guide to the List
In order to deeply implement General Secretary Xi Jinping's important exposition on new industrialization, implement the decision-making and deployment of the CPC Central Committee and the State Council on the empowerment of new industrialization by AI, and continuously deepen the "AI+" action, and strive to realize the beautiful blueprint of "three highs and four news", we now release the 2024 "AI+" integration application scenes guide. "Artificial Intelligence +" action, and strive to realize the "three high, four new" beautiful blueprint, is now released in 2024 "Artificial Intelligence +" fusion application scene unveiled guide.
Artificial Intelligence + factory
(a) + AI twin factory
Encourage manufacturing enterprises to comprehensively utilize the new generation of information technology, such as AI, digital twin, etc., to collect information from process and equipment. A new generation of information technology, collect multi-modal real-time data from processes and equipment, with the help of multifaceted model coupling capabilities, with a distributed computing framework to achieve the integration of simulation, optimization, and control, to build a factory digital twin model based on a complete set of physical factory production, warehousing, in-plant logistics, business management, etc., to carry out from the unit, the system, and the complex environment of the virtual reality mapping accuracy, integrated to adapt to the different scenarios, to achieve multi-dynamic, multi-functional and multi-modal real-time data collection. Artificial Intelligence model to achieve multi-link dynamic sensing, production process optimization, lean production management.
(2)＋5G factory
Encourage manufacturing enterprises to face the factory production and operation, testing and monitoring, operation management and other links, based on 5G industrial control computing power base, explore 5G independent private network, 5G hybrid private network, 5G virtual private network and other industrial-level 5G private network. The construction of industrial-level 5G private networks such as 5G independent private networks, 5G hybrid private networks, 5G virtual private networks, etc., and the integration and application of 5G URLLC, 5G TSN and other innovative solutions, to promote the extensive connection between the computing network and the production line level, workshop level, factory level business scenarios, to support the collaborative research and development and design, precise and dynamic operation, intelligent logistics in the factory, and other scenarios and applications, to form a 5G factory with a wide range of connection of the production unit, and a deep fusion of information technology and operation technology.
(3)＋Zero-Carbon Factory
Encourage manufacturing enterprises to face the demand for intelligent management and control of green low-carbon and energy-saving and emission reduction, and to build a digital integration platform based on the intelligent Internet of Things operating system, and relying on technologies such as artificial intelligence and digital twins. Build proprietary energy and carbon databases, organization-level and product-level carbon accounting, energy efficiency assessment and optimization models, establish equipment/production lines/workshops/factories multilevel energy consumption models and full-life cycle carbon emission models, realize the refined management of corporate carbon emissions and carbon footprint management of the full life cycle of the product, carry out carbon emission reduction of processes relying on carbon reduction technologies such as CCUS, and combine artificial intelligence algorithms with the prediction of corporate energy demand, tap emission reduction potential, and realize multi-system or multi-process carbon emission reduction. The company also uses artificial intelligence algorithms to predict the energy demand of the enterprise, explore the potential of emission reduction, and realize the balanced scheduling of energy consumption among multiple systems or equipments.
II. Artificial Intelligence + Manufacturing
(A) + Product Design
Encourage manufacturing enterprises to join hands with software service providers in software development, Design, operation and maintenance and other aspects of the general model based on the secondary development of research and operation of special large models, based on research and development and operation of the field of proprietary datasets and knowledge accumulation to build pre-training model, the use of high-quality industry labeled data on the pre-training model tuning, so as to develop independent and controllable research and operation of the industry large model, the formation of a variety of development and testing aids after the secondary training to realize the intelligent auxiliary design models, specialized Product design knowledge base, coding assistance, intelligent testing, intelligent operation and maintenance, specialized intelligent decision-making.
(2)＋Production process
Encouragement of manufacturing enterprises for the production and operation of the operating conditions of the combination of variable, high equipment failure rate and other practical problems, to create a unified platform for production management, self-research high-frequency digital mining on the site of the key equipment process Real-time collection and monitoring of parameters, through mathematical statistics, neural networks and other means to build the production process for different product indicators and feed nature, operating conditions and other feedback derived from the big model, based on artificial intelligence, industrial Internet and other technologies on the model of continuous iterative optimization, real-time optimization of the production program, the realization of intelligent scheduling, intelligent warehousing and logistics, predictive maintenance, and so on.
(3) + operations management
Encourage manufacturing enterprises to address the actual problem of low efficiency in operations management, warehousing and logistics, marketing and other aspects, establish a digital platform for operations management, using machine learning, computer vision, Environment perception and other intelligent network hardware and software technology, high concurrency data, multi-modal data, multi-source heterogeneous data and other elements of real-time collection of information, connecting business application systems, building operational decision-making algorithmic models, and carry out big data analysis, to achieve lean production, intelligent wind control, precision marketing and other intelligent applications in the plant environment and unmanned vehicles, drones and other terminal equipment in the warehousing, urban and other commercial applications in the environment outside the plant.
Three, artificial intelligence + products
(a) + humanoid robots
Encouragement of manufacturing enterprises for the logistics, factory manufacturing, hazardous environment operations and other complex, hazardous, repetitive robots. environment operations and other complex, dangerous, repetitive tasks, based on the physical entity of the humanoid robot, collaborative end-to-end multimodal large model and perception algorithms deployed in the edge server, the task command is converted into action commands, combined with a variety of sensor data, so that the robot end of the complex environment to complete the automotive assembly, equipment maintenance, material handling, and other specific actions to execute, relying on the application of scenarios to iterate and optimize the control algorithms, to Relying on the application scene iteration and optimization of control algorithms, it improves the environment perception and action control capability, and realizes cooperative control and human-machine interaction in complex environments.
(2) + industrial software
Encourage manufacturing enterprises to join hands with artificial intelligence service providers to extract and integrate large amounts of industrial data, technical documents and expert experience based on generative AI and other technologies, and to refine key process knowledge. To form a refined, practical and structured knowledge system, to carry out independent learning iterations for complex and changing industrial application scenarios such as intelligent scheduling, intelligent sorting, complex workpiece identification, etc., and to realize intelligent monitoring and guidance of the production process, industrial knowledge sharing and efficient collaborative decision-making.
(3) + digital tools
Encourage manufacturing enterprises to focus on the popularization and application of localized and independently controllable digital tools, and carry out localization transformation of digital software, systems and tools in use and under construction by enterprises, and to develop and implement digital tools based on localized cloud native architecture, microservice architecture and low-code architecture. Based on localized cloud-native architecture, microservice architecture, low-code development platform, combined with small models, knowledge mapping and other technology development applicable to the needs of the enterprise independent and controllable industrial SaaS applications, RPA, EDA tool chain and other digital tools and industrial model libraries, process libraries, process packages, and other special tools, to the large and medium-sized enterprises to comprehensively promote and realize the industrial application of the face of the popularity of the application.
Four, Artificial Intelligence + Services
(a) + Cloud Manufacturing
Encouragement of manufacturing enterprises to face the needs of users of large-scale personalized customization. To build a full-process data chain linking users, products, equipment, production lines and other multi-level, multi-plant, build intelligent decision-making and task allocation models based on AI, blockchain, cloud computing and other technologies, and carry out task distribution and parallel organization of design, supply, manufacturing and service links with the help of a cloud-based network collaboration platform, so that multiple customer demands can be delivered to multiple factories in parallel, and seamlessly interface with user demands and the manufacturing system to achieve efficient collaborative manufacturing, rapid and agile production, and to achieve a high degree of efficiency in manufacturing. This allows for efficient collaborative manufacturing, fast and agile production, and full-process control and traceability.
(2)+Digital Man
Encourage manufacturing enterprises to face the needs of marketing intelligence, integrate cutting-edge artificial intelligence and big data technology, and leverage the general capabilities of intelligent office assistants and digital man video production developed by software service providers to meet the needs of personalized marketing and other scenarios. The module, for personalized marketing and other scene needs, secondary development of professional functional areas, industry areas constitute the professional ability module, build artificial intelligence model, for pre-sales, sales, after-sales link distribution adapted to the needs of different scenes of the digital person, the use of personalized recommendation algorithms, intelligent customer service, the big model of the answer to the question and so on, to achieve the digital person empowered by the whole process of marketing.
(C) + data elements
Encourage leading enterprises and data service providers to jointly face the manufacturing industry management, R & D, production and other aspects of the integration of the production management system, testing systems and other industrial software systems, through standardized interfaces, Data mapping technology, etc., seamless docking and compatibility of data between different systems, based on digital object architecture, distributed ledger, cross-domain control, smart contracts and other technical systems, by limiting access to specific data authorization subject, through the enterprise, the safe flow of data between enterprises, to promote the distribution of sharing and platform centricity of the service between multiple subjects to achieve the pricing of data assets, networked production and so on.
(4) + Emerging Economy
Encourage manufacturing enterprises to join hands with digital enterprises to face the emerging fields such as industrial tourism, low-altitude economy, culture + equipment, intelligent driving, etc., relying on the 5G-A passive sense All-in-one, artificial intelligence computing power and other infrastructure, integration of AI, digital twin, VR / AR and other technologies, superimposed infrared, video recognition and sensor number mining, digital recovery of industrial scenes, virtualized display, low altitude air traffic control platform AI supervision and scheduling, etc., the development of industrial tourism dynamic prediction of passenger flow, personalized content generation in real time, eVTOL (Electric Vertical Take-Off and Landing Vehicle) distribution inspection, cultural tourism consumption and other new types of scenarios.
(E) + Advanced Intelligent Computing
Encourage manufacturing enterprises to join hands with intelligent computing centers and other computational power supplying bodies to meet the computational power needs of industrial large models and other intelligent application scenarios, and to develop a heterogeneous computing architecture with AI based on AI-specific computational power chips and acceleration chips. Heterogeneous computing architecture, artificial intelligence server as the core facilities, build open core algorithm model, breakthroughs in deep learning, force coupling and trajectory planning and other key technologies, to promote industrial scenarios and artificial intelligence arithmetic adaptive coupling, incubated based on the smart computing industrial machine vision, collaborative R & D and design, flexible manufacturing, predictive maintenance and other new smart computing industrial scenarios.
Nouns:
1. AI: Artificial Intelligence is a new technical science that researches and develops the theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence.
2. Digital Twin: refers to the simulation of the real world through digital models to complete the mapping in virtual space, thus reflecting the corresponding entity equipment full life cycle process.
3.5G: Fifth-generation mobile communications technology with high speed, low latency, and large connectivity, is the network infrastructure that realizes the interconnection of people, machines, and things.
4. URLLC: 5G low-latency, high-reliability communication, one of the three major application scenarios of 5G, is designed to support factory automation, remote control, and other services that are highly sensitive to latency and stability.
5. TSN: Time Sensitive Networking, a real-time Ethernet standard based on IEEE 802.1, aims to establish a time-sensitive mechanism for accurate network time synchronization.
6. TSN: A new type of information infrastructure for on-demand allocation and flexible scheduling of computing, storage, and network resources between cloud, edge, and end.
7. CCUS: Capture, Utilization and Storage, which captures and purifies carbon dioxide emitted during the production process and then puts it into new production processes for reuse and storage.
8. Big Model: refers to a machine learning model with a large number of parameters and a complex structure, capable of handling massive amounts of data and accomplishing a variety of complex tasks.
9. Humanoid robots: robots with human form and function, i.e., anthropomorphic limbs, motor and operational skills, and the ability to perceive, learn, and cognize.
10. SaaS application: SaaS refers to an application model that provides software services based on the Internet, and industrial SaaS is SaaS application software that is used in the industrial field.
11. RPA: Robotic Process Automation is a software robotics and artificial intelligence-based business process automation application that performs tasks according to self-designed processes.
12. EDA: Electronic Design Automation, refers to the use of computer-aided design to complete the functional design of ultra-large-scale integrated circuit chips, verification and other processes of the design method.
13. Digital human: refers to the artificial intelligence technology to simulate the human way of thinking and communication, with autonomous consciousness and learning ability of the virtual characters.
14. 5G-A: It is based on the evolution and enhancement of 5G, and is an information technology that supports the digital upgrading of industries such as 3Dization and cloudization of the Internet industry, and the integration of communication and perception.
15. VR: Virtual Reality, is a computer simulation system that allows the creation and experience of virtual worlds.
16. AR: Augmented Reality is a technology that calculates the position and angle of a camera image in real time and adds the corresponding image, video, and 3D model.
