What is the future development trend of China's manufacturing industry?

With the higher demand of market and policy orientation for enterprise production efficiency, the intelligent transformation of traditional manufacturing industry has become one of the core elements of China's economic development. In the future, smart equipment and industrial big data will be deeply integrated with traditional manufacturing, which will greatly improve the production mode of traditional manufacturing and release productivity.

The overall path to promote intelligent manufacturing proposed in the Plan is: based on the manufacturing essence, closely following the intelligent characteristics, taking technical equipment as the core, taking data as the basis, and relying on manufacturing units, workshops, factories, supply chains and other carriers, to build an intelligent manufacturing system that integrates reality with reality, is knowledge-driven, dynamically optimized, safe, efficient, green and low-carbon, and promotes the digital transformation, networked collaboration and intelligent transformation of the manufacturing industry.

Build the relevant data information model, and break through the four system integration technologies of production process data integration and cross-platform cross-domain business interconnection, cross-enterprise information interaction and collaborative optimization, intelligent manufacturing system planning and design, and simulation optimization. Develop new models such as scenarios, workshops, factories, multi-level intelligent design of supply chain, network collaborative manufacturing, large-scale personalized customization, * * manufacturing, and intelligent operation and maintenance services.

Strengthen independent supply, vigorously develop intelligent manufacturing equipment, and guide software, equipment and users to develop industrial software such as manufacturing, management, control and execution. Hightopo provides lightweight, easy to maintain and low-cost solutions for small and medium-sized enterprises for typical scenarios and sub-industries. The powerful visualization engine technology has created an intelligent and green visualization management mode for the digital intelligent manufacturing industry. It provides new ideas for enterprises that want digital transformation, such as intelligent workshops, intelligent assembly plants, construction machinery and equipment plants, automobile manufacturing, logistics and warehousing management and other industries.

By making the production process of the production line transparent, the production is orderly and controllable. Twin modeling analysis+data visualization scheme realizes the all-factor connection of digital factory, drives intelligent production with data, and greatly improves the efficiency of data utilization. Relying on the generalization of the above digital foundation, the same technical scheme can also be applied to more industries and enterprises that are undergoing industrial digital transformation.

Through the docking data interface, the business data of key equipment is visualized in the 3D scene, the status of key equipment is displayed in the page, and different equipment status is represented by different color equipment values and icons. Strengthen the infiltration of light manufacturing industry. Digital pairing is based on entity digital modeling, Internet of Things, big data, artificial intelligence and other technologies. By constructing a closed-loop data exchange channel between physical space and digital space, the objective mapping between digital space and industrial equipment is realized, and the real-time state of physical equipment in digital space is presented. In the future, digital pairing will strengthen the penetration of light industry manufacturing.

The core of intelligent manufacturing is to realize intelligent decision-making through deep integration and analysis of massive industrial data, and to improve the efficiency of resource allocation through new manufacturing modes such as flexible production, dynamic regulation and network cooperation.