Image generated by AIYXL using AI
A vision inspection system in a factory can identify part defects. But whether inspection results can promptly flow into rework, equipment maintenance and production scheduling determines how much business scope this capability can affect.
On October 26, the Equipment Industry Division I of the Ministry of Industry and Information Technology published the public notice of the 2026 Leading-level Intelligent Factory project cultivation list, with the public notice period running from October 27 to November 2. According to Xinhua News Agency, 34 projects are on the list, including Xiaomi Automobile Technology Co., Ltd.'s "AI-driven agile manufacturing high-end new energy vehicle super intelligent factory."
From individual tools to manufacturing systems
China carries out tiered cultivation of intelligent factories at four levels: basic, advanced, excellent and leading. The 2026 action notice requires that leading-level applicants must have already been rated as excellent-level intelligent factories, and must promote the widespread and deep application of new technologies such as artificial intelligence and explore changes in production methods and management models.
This gives the list an angle worth tracking: how enterprises connect scattered intelligent capabilities into a complete production process.
Take automobile manufacturing as an example: order changes may affect production scheduling, scheduling adjustments affect parts supply, and quality anomalies may require checking equipment and processes. AIYXL believes that in observing AI manufacturing, attention should be paid to whether information can flow between these links, whether decisions can be executed, and whether corrections can be made promptly after anomalies occur.
Beyond the list, what other evidence is needed
As of the end of September, China had cumulatively built more than 13,000 advanced-level and more than 500 excellent-level intelligent factories, and had cultivated 15 leading-level intelligent factories. These 34 projects are still at the public notice stage of the proposed cultivation list.
For subsequent cases, delivery lead time, first-pass yield, equipment downtime and energy consumption per unit of product are all indicators with more explanatory power than a vague "efficiency improvement." When comparing, the product mix, output and statistical period also need to be specified in order to determine where the change comes from.
This public notice provides a project entry point for continued observation. For each factory specifically, which processes have been connected, which decisions still require manual handling, and what improvements the investment has brought still await subsequent disclosure.
Sources: MIIT public notice · 2026 Intelligent Factory Tiered Cultivation Action Notice · Xinhua News Agency report