According to reports, on October 27, SAIC Volkswagen's new energy vehicle smart factory with a total investment of 17 billion yuan was put into production. In addition to automobiles, smart factories in the fields of home appliances and digital electronics are also emerging. However, experts believe that the current smart factories are mainly concentrated in discrete industries, and there are still relatively few smart factories in the process industry.

"Most of the content reflected in Industry 4.0 is related to discrete industries, and rarely involves process industries. Process industries have their own rules." A few days ago, the 682th academic symposium of the Xiangshan Science Conference focused on the physical systems and intelligence of manufacturing processes, and steel research. Yin Ruiyu, honorary dean of the Chinese Academy of Engineering and academician of the Chinese Academy of Engineering, said in an interview with a reporter from Science and Technology Daily during the meeting.

Process industry plays a pivotal role in the national economy
What is a discrete industry? What is the process industry?
"The manufacturing industry can be divided into two categories, one is the discrete industry and the other is the process industry." Yin Ruiyu told reporters.
Among them, discrete industries include equipment processing and manufacturing, such as automobile manufacturing, aircraft manufacturing, etc., which need to assemble and integrate different components; while process industries include metallurgical industry, chemical industry, building materials industry, pharmaceutical industry, etc., this industry is a These processes are carried out continuously, often connected to resources and energy at one end and products at the other end. The products can be used directly or further processed.

Yin Ruiyu pointed out that in process manufacturing industries such as chemical industry, metallurgy, building materials, etc., the physical nature of the dynamic operation of the manufacturing process can be expressed as: the material flow is driven and acted by the energy flow, in accordance with the set "procedures" such as production operation instructions. To perform dynamic and orderly operations along a specific "process network" and achieve multi-objective optimization, not just to produce products.

In his view, most of the process industries are basic industries and play a pivotal role in the national economy. Moreover, the process industry involves the input and output of material and energy, which has a great impact on the ecological environment.

The road to intelligence needs models and data to support
"In order to accelerate the deep integration of advanced manufacturing technology and information technology, and accelerate the continuous development of process manufacturing in the direction of intelligence, the Chinese Academy of Engineering has set up a consulting research project on the "2035-oriented process manufacturing intelligent goals, characteristics and path strategy research". Two typical process industries of steel and petrochemical were selected as the research objects, and the research put forward the development goals and ideas of intelligent process manufacturing." Yuan Qingtang, academician of the Chinese Academy of Engineering and consultant of the Science and Technology Committee of China Petrochemical Corporation, introduced.
Experts at the meeting told reporters that the domestic steel, petrochemical and other process industries have a relatively high level of automation and have a good foundation for intelligentization. However, the intelligentization of the process industry still faces many difficulties.
“How to straighten out the physical system and how to inject the information system into the physical system is technologically content, and all need models, data, sensing devices, etc. to support.” Yin Ruiyu still uses the steel industry as an example. First, the process of the steel plant The network structure should be further optimized, and the network of material flow, energy flow, and information flow should be further straightened out, so that these three can work together. At the same time, we need to improve modeling and software capabilities, and integrate various platforms and networks. These must be reflected in the engineering design, production operation, management and decision-making of the factory, and all need advanced technology to support.