The digital transformation of the automotive industry is accelerating
The Ministry of Industry and Information Technology, the Ministry of Education, the General Administration of Market Supervision, and the National Data Administration recently jointly issued the "Implementation Plan for the Digital Transformation of the Automotive Industry" (hereinafter referred to as the "Implementation Plan").
The person in charge of the relevant department said that the plan aims to promote the high-quality development of the automobile industry, takes intelligent manufacturing as the main direction, and deepens the integration and application of new generation information technology such as artificial intelligence with the automobile industry, which will help to improve the top-level design of transformation, guide the digital coordinated development of large, medium and small enterprises, and promote the high-quality development of the automobile industry.
Top-level design continues to improve
As an important pillar industry of the national economy, the automobile industry has a long industrial chain, a wide range of coverage and strong correlation, which is the key area of the digital transformation of the manufacturing industry. Accelerating the digital transformation of the automobile industry is an important measure to support the construction of a powerful automobile country, promote new industrialization, and cultivate new quality productivity.
Around the digital transformation of the automotive industry, a multi-level policy system has been built at the national level. The "15th Five-Year Plan" proposes to "promote technological transformation and upgrading, and promote the transformation of digital intelligence in the manufacturing industry". Documents such as the Development Plan for the New Energy Vehicle Industry (2021-2035) and the Work Plan for the Steady Growth of the Automotive Industry (2025-2026) have been issued to promote the in-depth application of artificial intelligence technology and guide the digital and collaborative transformation of the supply chain of the industrial chain.
At present, the digital transformation of my country's automobile industry continues to deepen, accelerating the evolution to digitalization, networking, and intelligence. However, there are still problems in the transformation process, such as insufficient top-level design, insufficient application of data elements, and slow transformation of small and medium-sized components.
Cui Dongshu, secretary-general of the National Passenger Car Market Information Association, analyzed that the lack of top-level design is reflected in the scattered enterprise strategy and inconsistent industry standards. The lack of application of data elements is reflected in weak data governance and low scene penetration rate. The slow transformation of small and medium-sized enterprises is due to the high transformation cost and lack of lightweight transformation scheme.
Zhao Jia, director of data governance research at the China Automotive Strategy and Policy Research Center, also said that the lack of a unified digital transformation roadmap in the industry and the repeated investment and construction of enterprises make it difficult to form a digital synergy of the whole industry chain. There are "data islands" within the enterprise and between the main body of the automobile industry chain, and the path of data flow and realization is not yet clear. In addition, most small and medium-sized spare parts enterprises only have basic communication capabilities and medium-sized enterprises and many "dumb devices" dumb devices, further increase the difficulty of transformation.
In response to these problems, the Implementation Plan has an all-round and multi-level layout. Through the establishment of a unified diagnostic system, the construction of a credible data space, and the implementation of SME empowerment actions, the pain points are accurately solved, and the entire industry chain is formed.
The relevant person in charge of the Equipment Industry Division I of the Ministry of Industry and Information Technology said that the current technological innovation in the automotive industry is changing with each passing day. Artificial intelligence promotes revolutionary breakthroughs in the automotive technology research and development paradigm, and the transformation of digital intelligence has become an important accelerator to promote the innovation and development of the industry. At the same time, as a carrier strategic emerging industry, intelligent network-connected new energy vehicles promote the overall digital transformation of the industry with great value, strong role and a wide range of driving forces. It is urgent to improve the top-level design of transformation through the Implementation Plan, guide the digital collaborative development of large, medium and small enterprises, and promote the high-quality development of the automotive industry.
Key tasks are clear and clear
Focusing on the digital transformation of the automobile industry, the Implementation Plan proposes two-stage development goals: by 2027, the maturity level of intelligent manufacturing capability of vehicle benchmark enterprises will be raised by one gear, the digital level of parts enterprises will be significantly improved, the penetration rate of R & D and design tools will exceed 95%, and the numerical control rate of key processes will exceed 70%; The overall labor productivity of the industry is 10% higher than 2025, and the product development cycle and delivery cycle are 20% shorter; create an intelligent factory model that can be replicated and promoted, and cultivate more than 20 industry intelligent manufacturing system solution suppliers. By 2030, the overall digital intelligence development of the industry will reach a high level, and digitalization and business will be deeply integrated.
Cui Dongshu analyzed that the quantitative index for 2027 is based on the current basic design of the industry: the penetration rate of R & D and design tools in 2025 will exceed 90%, and the numerical control rate of key processes will exceed 65%, with an average annual improvement potential of 1 to 2 percentage points. At the same time, with reference to the effectiveness of the transformation of head enterprises, combined with the target of enabling action for small and medium-sized enterprises in parts, the achievable improvement space is measured, taking into account the accessibility of the target and the traction of the industry.
In order to ensure the smooth achievement of the two-stage development goals, the Implementation Plan proposes to implement "six major actions", including diagnosis, evaluation and improvement, digital transformation of small and medium-sized auto parts enterprises, typical scenarios and artificial intelligence application demonstration, gradient cultivation of industrial entities and matrix construction, standard system improvement and interconnection guarantee, key technology research and basic capability strengthening.
Zhao Jia believes that the Implementation Plan accurately focuses on the difficulties and pain points of the digital transformation of the automotive industry: first, improve the top-level design and put forward a clear roadmap and timetable for the digital transformation of the automotive industry; The second is to excavate and release the value of data elements, list "fully release the value of data elements" as one of the overall requirements, and clearly improve the data security protection system and technical capabilities in the "key technology research and basic capability strengthening actions, ensure data compliance and efficient circulation; Third, special empowerment of small and medium-sized enterprises, the establishment of" auto parts small and medium-sized enterprises digital transformation empowerment action ", step by step to promote the transformation, focusing on promoting" dumb equipment "transformation and key equipment update.
The enabling action for the digital transformation of small and medium-sized enterprises has attracted the attention of auto parts enterprises. The person in charge of Zhejiang Wanan Technology Co., Ltd. said that the company has built a digital system framework, which will be further integrated to achieve interconnection. At present, the biggest problem facing digital transformation is the shortage of talents. The demand for composite talents (both mechanical, electronic and algorithmic capabilities) in automotive intelligence has surged, but there is an obvious imbalance in the regional distribution of high-end talents, and it is difficult for the region where the enterprise is located to attract top technical teams.
In this regard, the relevant person in charge of the Equipment Industry Division I of the Ministry of Industry and Information Technology stated that after the "Implementation Plan" is released, the Ministry of Industry and Information Technology will earnestly implement safeguard measures. For example, in terms of strengthening talent protection, we will deepen school-enterprise cooperation, implement the "academic education skills certification" training model, encourage the backbone of enterprises to enter the school to teach, improve the incentive mechanism for digital talents, improve the treatment of talents, and regularly carry out digital and intellectual exchange training to promote advanced experience.
Cultivate typical scenes
In order to provide reference and guidance for enterprises in the industry, the Implementation Plan has released a list of typical scenarios. Eight typical scenarios of digital intelligence, including intelligent collaborative research and development, model-based system engineering and flexible agile production, are proposed around the five links of research and development, production, supply chain, sales and service. The transformation objectives, implementation methods and required conditions are respectively proposed according to each scenario.
In the flexible and agile production scenario, the Implementation Plan proposes to dynamically optimize production plans through data-driven intelligent scheduling, relying on the industrial Internet platform to integrate order, equipment, and supply chain data, and using AI algorithms. Through intelligent scheduling in the workshop, intelligent warehousing and logistics, flexible configuration of production lines and other technologies, the rapid transformation of user needs and automated mixed production of a variety of products are realized, and customized products are delivered quickly and efficiently.
"BYD's intelligent vehicle manufacturing has reached the third level and is moving towards the fourth level." The relevant person in charge of BYD Group said that some of the scenarios have been predicted and optimized through data-driven, such as predictive maintenance of equipment, AI intelligent scheduling, quality prediction through process parameters, and logistics optimization. In the future, big data and AI capabilities will be used in more business scenarios to accurately control business. The person in charge proposed that the future of the underlying large model and computing power chips and other infrastructure to increase some support.
The head of Wanan Technology revealed that the digital requirements of the head vehicle enterprises for parts have shifted from "basic standards" to "deep coordination". For example, some car companies require suppliers to provide real-time data interfaces to support spatial download technology (OTA) upgrades and intelligent driving algorithm iterations. These requirements have driven the company's transformation from a single component supplier to a system-level solution provider, accelerating the mass production process of technologies such as electronic mechanical braking (EMB) and wireless charging. At the same time, the requirements of car companies for supply chain transparency have also prompted companies to introduce blockchain technology to achieve full-process data traceability. (Reporter Liu Jin)
Information source: Economic Daily
