According to the evaluation results of the “Global Intelligent Manufacturing Development Index Report”, the United States, Japan and Germany rank in the first echelon and are the “leading” countries in the development of intelligent manufacturing, while China is tied for the second echelon with the United Kingdom, South Korea and Canada. “Advanced” countries for manufacturing development.

  As we all know, China has already proposed “Made in China 2025” in 2015. The key strategy is “intelligent manufacturing”, which is “Industry 4.0”. The first goal is to become a manufacturing power in 2025. If the so-called “manufacturing power” refers to a “leading country”, it means that my country needs to successfully promote from the second echelon to the first echelon within the next five years.

  This task is not easy. Having said that, is there a best path that can speed up the realization of the goal while eliminating some existing problems and hidden dangers in the future?

Towards “Industry 4.0”: not simply a crude “machine for humans”

  From the slogan “Made in China 2025”, almost five years have passed.

According to the sample cities collected in the “World Intelligent Manufacturing Center Development Trend Report (2019)”, the overall average output value of smart manufacturing is 1.14 trillion yuan. In terms of smart manufacturing production, only 18 cities in the world exceed this level. China occupies 7 places, among which Suzhou is ranked first, entering the top ten list together with Foshan.

  Behind this beautiful report card, we have seen the results of the efforts of the government, down to various cities, parks, and enterprises, but also a hidden topic—intelligent manufacturing talents.

  In the development of intelligent manufacturing, one of the most obvious trends and phenomena is “machines for humans.” Data shows that in traditional processing and assembly enterprises, 500 errors occur for every 1 million manual operations performed on average, while the error rate of robots is only 11.5, which is only 2.3% of that of humans.

  Previously, the Oxford Institute for Economic Research also predicted that in the next 10 years, robots will replace 20 million manufacturing jobs worldwide. Each new robot entering the labor market means that 1.6 manufacturing workers will be replaced.

  I still remember that in 2016, the manufacturing giant Foxconn successively fired 60,000 workers at the Kunshan factory, replacing those on duty to become robots. At that time, Guo Taiming also announced to the public that he would replace 80% of workers with robots within five years and actively move closer to “industry 4.0”.

It is reported that as of the end of 2018, Foxconn has transformed a number of “light-off factories”, reducing the number of workers on a single production line from three digits to double digits, a decrease of nearly 90%, but the overall production capacity has increased by 18% and manpower consumption has been reduced by 84%. , To achieve a reduction of 11% in manufacturing costs per million of revenue and 8% in management costs.

Looking at it now, it seems that the effect of “machines for humans” is quite good, but we should also notice that Foxconn has no plan to replace all humans with robots, but still leave a little Some people.

  Why? Because “100% robots for humans” is not the essence of intelligent manufacturing, or industrial 4.0. No matter how high the automation rate is, several humans are needed next to the machine. It’s just that, in an ideal state, these humans are no longer doing simple manual mechanical tasks, but supervising, debugging, and repairing robots, which is the so-called “intelligent manufacturing talent.”

Towards Industry 4.0: Training of “ignored” talents

On the issue of “talents”, especially those who master a certain cutting-edge technology such as artificial intelligence, and the production characteristics, processes, and processes of the manufacturing sub-industry, not only small and medium-sized enterprises, but large enterprises, most It has not reached saturation.

  Previously, data has predicted that the demand for talents in the smart manufacturing field will be 7.5 million in 2020, and the talent gap is predicted to be 3 million. By 2025, the talent demand is predicted to be 9 million and the talent gap is predicted to be 4.5 million.

  In short, there are few high-tech talents in the existing intelligent manufacturing talent team in my country, and it is difficult to meet the relevant needs of transformation and upgrading to evaluate the overall quality.

It is undeniable that in the past year or so, there have been repeated questions about “talents”. However, nearly 90% of the topics focused on AI talents and semiconductor talents, and the remaining 10% or so did not all fall on them. Intelligent manufacturing talents.

It can be seen that due to the lack of AI talents, major universities have successively established AI colleges and AI majors, and have been upgraded to first-level disciplines; because of the lack of semiconductor talents, after upgrading to first-level disciplines, some companies have chosen to jointly establish independent universities with universities… Intelligent manufacturing.

  In response to this problem, Nanjing took notice.

  Last year, in Nanjing’s “Rooting Visit” event aimed at building a globally influential and innovative city, Kirin Technology Park went to Hannover, Germany, and signed a cooperation with the group to build Nanjing Intelligent Manufacturing Institute.

At the end of November this year, the Nanjing Institute of Intelligent Manufacturing, which was built by Kirin Science and Technology Park in collaboration with Nanjing University of Science and Technology, Haier Kaos, and the German Institute of Intelligent Manufacturing to reflect the important achievements of Sino-German intelligent manufacturing cooperation, has also been officially opened. This is also the first in China. An independent college for the cultivation of professional talents established by Sino-foreign cooperation.

In the future, based on the Yangtze River Delta, the college will introduce German 4.0 technological achievements, corporate resources, foreign cooperation, etc., and through cooperation with intelligent manufacturing companies, create a “production, learning, research, transfer, and innovation” intelligence Manufacturing engineering elite training and achievement transformation platform is expected to train 3,000 intelligent manufacturing talents each year.

For the current gap of millions of smart manufacturing, it may not be enough to output 3,000 talents. However, from the perspective of domestic smart manufacturing talent training, the establishment of Nanjing Smart Manufacturing Institute will also play a demonstrative role for future related colleges. Make an example of establishment and cultivation of talents.

As one of the co-founders and a leading domestic intelligent manufacturing enterprise, from the perspective of the enterprise, Ren Xueliang, general manager of Kaos COSMOPlat education ecology, said that the school’s scientific research system is still traditional and cannot be fully adapted to the training of intelligent manufacturing talents. Therefore, this system needs to be restructured. This factor is also frequently mentioned in the training of AI talents and semiconductor talents.

Taking the establishment of Nanjing Intelligent Manufacturing Institute as an example, Ren Xueliang said that the establishment of such academies, in addition to shouldering the responsibility of “talent export”, starting from the national level, can also be said to have opened up the “last mile”-cultivating compound talents At the same time, it also helps companies shorten the training cycle for new employees and reduce time, cost and energy expenditure.

  Forecast the future, as the intelligent transformation and upgrading of enterprises continues to advance, the phenomenon of “machines for people” will inevitably become more common. By then, it will no longer be the bustling workers working on the assembly line, but the engineers in twos and threes.

  To achieve the above scenarios, the cultivation of intelligent manufacturing compound talents is inevitable and extremely important. Among them, more targeted colleges, especially those with leading intelligent manufacturing companies participating in running schools and providing platforms, will be able to effectively promote the cultivation of high-end talents and improve the echelon construction of talents in various key fields of intelligent manufacturing.

 

  At last  

Is there really the best path toward industry 4.0 and toward intelligent manufacturing? It is difficult to have, all the paths are to move forward slowly and then come out.  Compared with the best path, the most effective path actually exists. There are three key points: high-end technology research and development, application scenarios landing, and compound talent training. The combination of these three represents the infrastructure construction of the intelligent manufacturing industry.