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How to break through the difficulty of deep integration between artificial intelligence and manufacturing

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Update time : 2019-12-04 20:00:11
According to research and analysis, it is estimated that by 2035, due to the application of artificial intelligence, the added value growth rate of the manufacturing industry can increase by about 2.0%, which is the largest increase among all industrial sectors. It can be seen that the large-scale application of artificial intelligence in the manufacturing field is very critical. To further promote the deep integration of artificial intelligence and manufacturing, at this stage, we must attach great importance to the main difficulties affecting the deep integration of artificial intelligence and manufacturing, and strive to make breakthroughs.

1. It is difficult to develop and utilize manufacturing data

The deep integration of artificial intelligence and manufacturing needs to be based on big data. Compared with the consumption link, the availability, universality, and developability of data in the manufacturing link are significantly weaker. The data generated by manufacturing machinery and equipment is usually more complex, and the data is irrelevant. In addition, the data in the manufacturing process requires the installation of a large number of high-precision sensors, which not only requires huge investment in the early stage, but also daily maintenance and labor costs in the later stage of maintenance.

In this regard, a large industrial database in the manufacturing process can be constructed. The industrial field is dominated by enterprise private databases, and the data scale is limited and the data quality is not high, which seriously restricts the "self-learning" of artificial intelligence in the industrial field. To achieve the deep integration of artificial intelligence and manufacturing, it is necessary to strengthen data acquisition and integration in the manufacturing field. Based on the company's private database, build the world's largest and largest manufacturing large database, and gradually form an independent standard system to improve labor. Intelligent security and stability.

2. Lack of core artificial intelligence technology

Although the development of China's artificial intelligence in the field of commercial applications is at the forefront of the world, the most critical and core technologies that support the deep integration of artificial intelligence and manufacturing are still controlled by developed countries, and devices and production equipment are mostly developed and produced by developed countries. .

In this regard, it is necessary to encourage superior manufacturing companies to strengthen their research on core technologies and key technologies with leading international artificial intelligence companies based on their application technology advantages, huge domestic market, huge potential profit margins, and strong capital strength. Development cooperation. Encourage leading manufacturing companies to jointly establish artificial intelligence R & D institutions overseas to strengthen scientific and technological cooperation and information exchange, in order to make full use of innovative resources such as international technology, capital, and talents, and improve their R & D capabilities in core technologies and key technology areas.

3. There is a serious shortage of compound talents required for the deep integration of artificial intelligence and manufacturing

For a long time, high-end artificial intelligence talents are usually concentrated in the software and Internet industries, and the personnel in charge of informatization in the manufacturing sector have an inaccurate and incomplete understanding of artificial intelligence concepts and technology, which is difficult to support manufacturing enterprises. Intelligent transformation and upgrading. From the perspective of talent supply, at this stage, there is a serious shortage of composite talents who not only understand manufacturing technology and development laws, but also master key technologies in artificial intelligence, and are also capable of application development. Although some universities at home and abroad have begun to set up artificial intelligence majors or courses, artificial intelligence teaching content for the manufacturing industry is still scarce.

In this regard, in a short period of time, the relevant disciplines that have been directly affected by the deep integration of artificial intelligence and manufacturing can be adjusted to expand the proportion of skills-based and knowledge-based vocational education. Add intelligent manufacturing-related courses and majors in university education, set up disciplines reasonably, improve the compilation of teaching materials, and form a teaching system as soon as possible. Education expenditure at all levels is inclined to intelligent manufacturing-related majors, and at the same time reform the technical education system to meet the demand for technical talents in the era of artificial intelligence.
https://www.infignos.com/templates/updatelistingnow.cfm?email=ryanlee901213@gmail.comShenzhen Kangda Precision Manufacturing Co.,Ltd.,Machining Manufacturer,Shenzhen,FL