The Ministry of Industry and Information Technology, the State owned Assets Supervision and Administration Commission of the State Council, and the All China Federation of Industry and Commerce recently jointly issued the "Implementation Guidelines for Digital Transformation of Manufacturing Enterprises" (hereinafter referred to as the "Guidelines"), which proposes a digital transformation path from four aspects: formulating transformation plans, organizing implementation, conducting effectiveness evaluations, and promoting iterative optimization. The aim is to fully stimulate the transformation momentum of manufacturing enterprises themselves and systematically and gradually promote digital transformation.
Experts say that in response to the problems of inconsistent standards, lack of composite talents, and uneven service provider capabilities in enterprise digital transformation, the "Guidelines" can help improve policy guidance, standard specifications, financial support, talent cultivation and other support guarantees, guide digital elements to gather in manufacturing enterprises, and form a joint force for promoting transformation.
Focus on solving non transferable problems
At present, the digital transformation of China's manufacturing industry is evolving from concept popularization to large-scale promotion. The problem of enterprises' unwillingness to transform has been preliminarily solved, but most enterprises still face problems such as unclear transformation needs, unclear transformation paths, and immature transformation solutions. "Not being able to transform" has become a key bottleneck.
Zhao Gang, the director of the Saizhi Industry Research Institute, analyzed that "not being able to transform" is determined by the complexity of digital transformation. Digital transformation is a data-driven business transformation process, and many enterprises do not know how to use digital technology to achieve business innovation in multiple scenarios such as design, manufacturing, supply chain, and management to solve pain points and difficult problems. Digital transformation is a continuous iterative system process, and many enterprises are accustomed to directly purchasing technology solutions and are not good at continuously improving transformation effectiveness according to the path of planning, implementation, evaluation, and iterative optimization. Digital transformation is a process of innovative application of digital technology, and many enterprises are not familiar with new technology solutions such as artificial intelligence, big data, blockchain, etc., and do not know how to integrate these technologies to maximize their technical application efficiency.
The relevant person in charge of the Information Technology Development Department of the Ministry of Industry and Information Technology introduced that in response to the weak digital foundation and lack of systematic strategic planning capabilities of enterprises, the "Guidelines" guide enterprises to formulate digital transformation plans, clarify transformation directions and goals, and promote digital transformation step by step from point to surface, from shallow to deep, and from easy to difficult; In response to the complex and diverse transformation scenarios, and the difficulty for enterprises to form a comprehensive understanding of the transformation, the "Guidelines" focus on common problems on the demand side to identify the entry points for transformation, build a systematic digital transformation scenario map by industry, cultivate functional universal tool products, and use the "sum" of scenario transformation to form the "solution" for the overall transformation of enterprises.
Zhao Gang believes that the "Guidelines" emphasize scientificity, follow model-based systems engineering, and refer to the classic cycle management theory PDCA (Plan, Execute, Check, and Handle) process in management to propose a methodological system for enterprise digital transformation; More emphasis is placed on phased and scenario specific implementation, proposing that digital transformation should be organized and implemented step by step, focusing on breakthroughs in various scenarios, and implementing strategies such as chain transformation of leading enterprises, overall transformation of large enterprises, and hierarchical transformation of small and medium-sized enterprises; More emphasis is placed on operability, which includes implementation principles, main tasks, and policy guarantees, as well as scenario reference architectures and typical scenario examples presented in the form of attachments.
Based on practical differentiation transformation
The "Guidelines" roughly divide manufacturing enterprises into three categories: industry leading enterprises, large enterprises, and small and medium-sized enterprises based on their differentiated characteristics such as digital foundation and enterprise scale.
Among them, most leading enterprises in the industry have a good digital foundation and relatively mature digital transformation experience within the company. The next stage of transformation focuses on improving the efficiency of industrial chain collaboration and the level of supply chain integration collaboration, consolidating their market dominance. Leading enterprises can build an industrial Internet platform for industries and industrial clusters, build a digital base that connects tool chain, data chain and model chain, create an open and shared industrial transformation ecosystem, improve the efficiency of manufacturing resource allocation, and enhance the resilience and risk prevention ability of the industrial chain supply chain.
The digital transformation of large enterprises focuses on integrating the existing digital basic capabilities, formulating the overall transformation plan with systematic thinking, improving the capabilities of data collection, knowledge precipitation, business connection, ecological construction, etc. through the construction of an industrial Internet platform, promoting the internal digital transformation of the whole process, whole scene, and whole chain, and realizing data driven intelligent production decision-making and in-depth optimization of operations.
Small and medium-sized enterprises have weak digital foundations and lack overall transformation capabilities. They should adhere to adapting to their own needs, focusing on breakthroughs, evaluating the potential value and feasibility of transformation, and clarifying transformation priorities. Specialized and innovative "little giant" enterprises can transform into more complex scenarios such as product digital twins and integrated design and manufacturing. Specialized and innovative small and medium-sized enterprises, as well as large-scale industrial small and medium-sized enterprises, will implement deep transformation and upgrading based on core scenarios. Small and micro enterprises, combined with their own resource conditions, carry out inclusive cloud based data empowerment, achieve the migration of business systems to the cloud, and improve their business management level.
Zhao Gang analyzed that different enterprises need to adopt different digital transformation strategies due to different industry types, enterprise sizes, business pain points, and digital processes. For example, small and medium-sized enterprises with insufficient digital investment should combine their business characteristics, take the core scenario as a breakthrough, and make full use of subscription products and services such as cloud based R&D design, production management and operation optimization of the industrial Internet platform to enhance their core competitiveness.
Liu Mo, Director of the Institute of Information Technology and Industrialization Integration at the China Academy of Information and Communications Technology, analyzed that chain transformation has become the main driving force for promoting the popularization of digitalization in small and medium-sized enterprises. Especially, as the supply chain control of leading enterprises extends from primary suppliers to secondary and tertiary suppliers, and shifts from production and sales coordination to dynamic monitoring, prediction, and scheduling optimization of the supply chain, the demand for digital capabilities of upstream and downstream small and medium-sized enterprises continues to increase, promoting the acceleration of their transformation process. In addition, the collaboration between leading enterprises and upstream and downstream small and medium-sized enterprises has expanded from simple component supply to more areas such as collaborative research and development and production cooperation.
The transformation model of industrial cluster parks has shifted from information integration to capability sharing, "Liu Mo gave an example. Previously, many industrial parks carried out market information and software tool integration and sharing through public service platforms, but now it has further extended to key capability sharing, empowering core processes such as research and development and production. For example, the rubber tire characteristic industry cluster area has created a digital shared mixing workshop, empowering more than 20 small and medium-sized enterprises.
Artificial intelligence becomes a key force
Qi Guangpeng, chairman of Inspur Yunzhou Industrial Internet, introduced that the "integrated equipment for artificial leather surface defect detection" built by Inspur Yunzhou, which integrates the self-developed intelligent algorithm research and development cloud platform and edge artificial intelligence reasoning engine, has a detection speed of up to 30 meters/minute, a minimum recognition accuracy of 0.1 mm, a defect detection rate of 99% and a stable detection level, can help enterprises avoid the risk of missing and false detection in manual detection. At present, it has been widely used in Zhejiang, Jiangsu, Fujian, Anhui, Hebei and other leather industry clusters, promoting the deep integration of artificial intelligence and manufacturing, and accelerating the intelligent upgrading of the leather industry.
Artificial intelligence is the most important driving force for digital transformation and intelligent upgrading in the manufacturing industry. It has been widely applied in the entire process of research and development, production, and management, with hundreds of scenarios and modes emerging, and forming two technological application routes. With the continuous progress of artificial intelligence technology and the expansion of application scenarios, the manufacturing industry will usher in greater development potential and opportunities, "said Liu Mo.
The "Report on the Development of Artificial Intelligence (2024)" released by the China Academy of Information and Communications Technology shows that artificial intelligence empowers new industrialization to develop in depth, presenting stage characteristics such as "collaboration of large and small models" and "fast at both ends, slow in the middle". Overall, specialized intelligent applications represented by traditional small models are gradually maturing, while general intelligent applications represented by large models are in the initial exploration stage. The continuous integration of artificial intelligence applications with industry scenarios is expected to profoundly transform manufacturing processes, organizational structures, research and development models, and product forms, thus opening up a new path for China's industry to grow from large to strong.
Zhou Hongyi, founder of 360 Group, believes that China's AI big model has broad development prospects, but to win the initiative in the global big model industry competition, we should give full play to China's institutional advantages and compete with foreign general big models; We also need to fully utilize the advantages of China's complete industrial categories and numerous scenarios, combine large models with various application scenarios, and promote a new industrial revolution. This is the key to achieving "overtaking on the bend" in development.
Data shows that currently, the digital transformation of traditional industries in China is steadily advancing. A total of 421 national level intelligent manufacturing demonstration factories have been cultivated, more than 10000 provincial-level intelligent factories have been built, and 13 Chinese enterprises have been newly selected as global "lighthouse factories". The total number of "lighthouse factories" in China has reached 72, accounting for 42% of the world's total. There are over 4500 core AI industry enterprises, nearly 200 generative AI service models that have been registered and launched to provide services to the public, and over 600 million registered users.
The recently held National Conference on Industry and Information Technology proposed that by 2025, the Ministry of Industry and Information Technology will adhere to the coordination of "point, line, and surface", accelerate the full coverage of digital transformation of industrial enterprises above designated size and specialized, refined, and new small and medium-sized enterprises, formulate digital transformation guidelines for key industries with "one industry, one policy", and build 200 high standard digital parks within three years; Layout a number of manufacturing digital transformation promotion centers by industry and region; Promote the construction of industrial 5G independent private network and strengthen the systematic industrial Internet platform system at most levels; Implement the "Artificial Intelligence+Manufacturing" initiative, strengthen the research and development layout of general and industry models, and apply them in key scenarios; Promote the research and application of basic software and industrial software technologies throughout the entire chain, and accelerate the construction of an advanced computing industry system.