At present, the digital transformation of the equipment manufacturing industry is extremely urgent, and new industrialization has become the inevitable path for high-quality development. The 2025 government work report also places great emphasis on developing new quality productive forces in accordance with local conditions, vigorously promoting new industrialization, and accelerating the digital transformation of traditional manufacturing industries. Among them, building smart factories has become the key to the digital transformation and upgrading of equipment manufacturing and enhancing its competitiveness. By taking digital transformation courses, conducting research on enterprises such as Dahua, Hengsheng Electronic, Qiangnao Technology, and SenseTime, and conducting on-site teaching, the author has explored the experience models for the construction of smart factories.

Analysis of the Existing Deficiencies in the Equipment Manufacturing Industry

The core competitiveness of the enterprise is insufficient. In the field of heavy equipment manufacturing, the traditional factory model generally suffers from problems such as low production efficiency of products and the lack of real-time monitoring of product quality control. More crucially, enterprises gradually lose their core competitiveness in market competition due to their inability to collect and analyze market information in a timely manner and accurately grasp the direction of innovation.

The degree of industrial agglomeration and the integrity of the industrial chain are not satisfactory. At present, due to insufficient concentration and an incomplete industrial chain, the equipment manufacturing industry faces challenges for enterprises in obtaining key components and technical services needed for intelligence. This not only increases the cost of building smart factories but also prolongs the construction period.

There is a shortage of digital talents As the equipment manufacturing industry moves towards intelligence, there is a significant shortage of digital talents in equipment manufacturing enterprises. This has put enterprises in a difficult situation in the application of advanced technologies and system operation and maintenance, making it hard for them to fully leverage the potential advantages of intelligent factories.

Three paths for smart factories to address industry pain points

Breakthrough in core competitiveness, moving from "traditional manufacturing" to "intelligent manufacturing". Relying on the automated and intelligent production mode, we can enhance production efficiency, reduce human errors, improve product quality, and thereby strengthen the competitive strength of our products in domestic and international markets.

The industrial chain is upgraded in a coordinated manner to build a "1+N" industrial ecosystem. Attract the aggregation of upstream and downstream enterprises, improve the upstream and downstream industrial chains, drive the development of surrounding service industries, and facilitate the upgrading of the equipment manufacturing industry.

Reconstruct the talent ecosystem and build a multi-subject collaborative training system. Strengthen cooperation with universities and research institutions, carry out talent cultivation and technological research and development cooperation projects, and cultivate compound talents that meet the needs of enterprises.

The "Three-stage eight-step" experience paradigm for the construction of smart factories

By distilling and integrating the methodologies of benchmark intelligent factory construction practices such as Dahua and Dongfang Electric, and combining the construction experience of Jinan No.2 Machine Tool's intelligent factory for structural components in Yucheng, a scientific and systematic intelligent factory construction system has been formed, covering three stages and eight key links.

Phase One: Strategic Foundation Laying. Planning: Follow the principle of "high aspirations but low capabilities". Clarify the construction goals and development directions of the smart factory. According to the maturity assessment model of intelligent factories, the planning should be "high-minded", clearly defining the construction tasks and indicators. To implement the principle of "low hands", we should start from the actual situation and proceed step by step. We should begin with the basic information construction and gradually promote projects such as the intelligent transformation of equipment and the construction of automated production lines. Current situation: Construction of a three-dimensional diagnostic system. Establish baseline data from three dimensions: equipment, process, and data. At the equipment level, understand the degree of automation, operational status of existing equipment, and the interconnection and interoperability among devices. In terms of processes, conduct an in-depth analysis of whether there are any redundant links in the enterprise's production and management processes. At the data level, clearly define the current status of data collection, storage, analysis and application.

Phase Two: System Construction. Determine the path: Implement the "targeted breakthrough" strategy. In accordance with the principle of "pain point priority and benefit orientation", priority should be given to transforming the links with high return on investment. Specifically, adopt the "targeted thinking", take the core business as the breakthrough point, and advance from point to area. First, accurately identify the key pain points and demands, quickly launch the intelligent transformation project (i.e., "shoot first"), and then summarize experiences during the implementation process and optimize and adjust the plan based on the actual situation (i.e., "aim later"). Integrating technology: Creating "AI+OT" integrated scenarios. Integrate artificial intelligence technology into key application scenarios. In the design stage, AI-assisted modeling tools are utilized to shorten the design cycle. During the production and manufacturing stage, visual small models are deployed for quality inspection to enhance the detection rate of welding defects. AI is utilized to analyze data such as equipment vibration for predictive maintenance, providing early warnings of faults and reducing downtime. Establish an organization: Set up an "Iron triangle" promotion mechanism. Form a leading group headed by the CTO, a joint execution team for IT and manufacturing, and an external expert advisory group, and establish a biweekly review mechanism. At the same time, an organizational structure for the construction of an intelligent factory should be established, clearly defining the responsibilities and divisions of labor of each department and personnel during the construction process. In addition, an external expert team is introduced as advisors to provide professional guidance for the construction process and ensure the efficient operation of the organization.

Phase Three: Continuous operation. Cultivating talents: Building a "pyramid-shaped" training system. Establish a three-level training system for digital "craftsmen - technical experts - leading talents" : Internally, strengthen employee training, regularly organize digital technology training courses and exchange activities, and encourage employees to learn and improve independently. At the same time, establish a talent incentive mechanism to attract and retain digital talents. Shaping Culture: Cultivating a "data-driven" operation mechanism. Establish a complete operation and management system for intelligent factories, conduct real-time monitoring and data analysis on aspects such as equipment operation, personnel performance, quality control, and cost management during the production process, and continuously optimize the operation mode of intelligent factories based on the data analysis results to achieve "accumulation for a sudden burst" and fully leverage the benefits of intelligent factories. At the same time, foster a data-driven decision-making culture and a team collaboration culture to create a favorable cultural atmosphere for the successful delivery and continuous iteration of smart factories. Evaluation: Build a "three-dimensional" assessment system. Set specific quantitative indicators from three dimensions: economic benefits (cost reduction rate, ROI), operational efficiency (OEE improvement rate), and sustainable development (energy consumption reduction rate) to evaluate the effectiveness of smart factory construction. During this process, enterprises must always be driven by efficiency, conduct thorough cost-benefit analysis, and ensure that the intelligent transformation project brings actual value.