Intelligent manufacturing can tap tech potential

Editor's note: Developing intelligent manufacturing is essential to capitalize on the ongoing scientific and technological revolution and gain new advantages in industrial competition. Xinhua News Agency spoke to Ouyang Jinsong, chief scientist at the Instrumentation Technology and Economy Institute on the future of intelligent manufacturing. Below are excerpts of the interview. The views don't necessarily represent those of China Daily.

The promotion of new-generation intelligent manufacturing aims to build systems that are capable of self-perception, self-learning, autonomous decision-making, self-execution and self-adaptation. It also seeks to develop smart factories that optimize the allocation of resources and industry and supply chains, fostering deeper integration and enhancing value creation.

Evolving consumption and production patterns are pushing manufacturing away from a relatively "symmetrical" model, in which production is organized around predictable and standardized demand, toward a model that demands rapid and increasingly asymmetric responses to changing market needs.

At the same time, as the physical and digital worlds become increasingly intertwined, manufacturing resources will be dynamically allocated and collaboratively optimized across enterprises, industries and geographical regions.

Recent international practices in intelligent manufacturing offer several useful reference points.

First, the development of next-generation intelligent manufacturing must remain grounded in the physical manufacturing sector. Digitalization and intelligence must not be pursued in isolation from real-world production.

Second, building data platforms that connect manufacturing resources across enterprises, industries and regions is a common development goal.

Third, global technological competition will increasingly involve manufacturing scenarios and manufacturing systems, emphasizing the importance of an organization's ability to coordinate and integrate resources across systems.

Going forward, in the 15th Five-Year Plan (2026-30) period, the development of new-generation intelligent manufacturing should focus on five key areas and advance through coordinated, systematic efforts.

First, greater attention should be paid to manufacturing knowledge, carriers and tools. Intelligent industrial software should transition from "human creativity supported by machines" to a model of "human needs, AI-generated ideas and human-machine collaboration".

The tiered cultivation of smart factories should address connectivity and interoperability bottlenecks, while the digital upgrading of equipment should create a new value system combining physical equipment and data assets.

Second, a robust data foundation should be established. Key technologies such as Asset Administration Shell, the Open Platform Communications (OPC) Unified Architecture for open-platform communications and digital product passports should be leveraged to build industrial data spaces and develop trusted, interoperable cloud-based industrial infrastructure.

Third, advanced manufacturing processes must remain the cornerstone of intelligent manufacturing. Manufacturing technologies should be pushed toward four frontiers: extremely large-scale, extremely small-scale, highly interdisciplinary and extreme-environment applications.

Fourth, AI should be more deeply integrated into core industrial applications. With the world's most comprehensive industrial system, China's industrial application scenarios and vast data resources provide a strong foundation for addressing the core challenges of physical AI. Industrial scenarios should serve as testing grounds for AI capabilities, accelerating AI technologies and promoting their safe application.

Fifth, an efficiency-oriented evaluation and service system should be established, including an "intelligent manufacturing efficiency index" with indicators at the product, factory, production-line and equipment levels. These indicators can be normalized and weighted to generate a comprehensive assessment of intelligent manufacturing performance.

Such an evaluation system would provide a basis for differentiated assessment and create stronger incentives for enterprises to enhance efficiency, fostering greater momentum for intelligent transformation.