Accelerate obvious large enterprises to drive industry upgrades (Economic Focus · Decoding Intelligent Manufacturing)
General Secretary Xi Jinping pointed out that the world is entering a period of rapid development of the digital economy. New technologies, new formats, and new platforms such as 5G, artificial intelligence, and smart cities are booming, which profoundly affects global technological innovation, industrial structure adjustment, and economic and social development.
In recent years, China has actively promoted digital industrialization and industrial digitization, and promoted the deep integration of digital technology with economic and social development.
Since 2018, Zhejiang has fully implemented the “No. 1 Project” of the digital economy with “digital industrialization and industrial digitization” as the main line.
More and more manufacturing companies are leveraging on advanced equipment, big data and cloud computing to develop smart manufacturing, and have found a new way to improve quality and efficiency, and develop high-quality.
A few days ago, the reporter visited Ningbo, Shaoxing and Hangzhou in Zhejiang to observe the development vitality and practical exploration of local intelligent manufacturing.
Starting today, this edition launches a series of reports "Economic Focus · Decoding Intelligent Manufacturing", so stay tuned.
--editor
Product quality requirements are higher, labor cost pressures are greater, and market competition continues to increase. For manufacturing companies in fully competitive industries, promoting quality and efficiency is an urgent proposition.
In Ningbo, Zhejiang, the local area continues to promote industrial digitalization, networking, and intelligent transformation, upgrading and expansion, providing support for the transformation and upgrading of manufacturing enterprises.
The data shows that in 2020, the growth rate of industrial investment and technological transformation investment in Ningbo will increase by 10.3 and 12.1 percentage points respectively over 2018.
Among them, represented by large-scale manufacturing enterprises, Ningbo Intelligent Manufacturing is accelerating towards a single-point breakthrough and leading-driven direction.
Transformation effect——
Optimize the production process, reduce cost, improve quality and increase efficiency
In the second plastic workshop of the Oaks home appliance production base, there are very few workers.
The plastic particles enter the injection molding machine along the pipeline of the centralized feeding system. The injection molding machine passes through the mold to complete the steps of injection molding, holding pressure, cooling, mold opening, ejection, and pickup, and then automatically transfers to the hot stamping machine to complete the hot stamping.
The production process takes less than two minutes from plastic pellets to shells.
Intelligent manufacturing optimizes the production process of the enterprise, realizes the improvement of quality and efficiency, and also has a positive impact on energy saving and consumption reduction, and green development.
Walking into the park of Ningbo Jintian Copper (Group) Co., Ltd., a greenery looms over your face. The trees are verdant, tall and lush, as if you are in an ecological garden.
It is hard to imagine that, as a copper processing company, the production workshop of Jintian Copper is also located in this green park.
This is a garden factory and also a smart factory.
Based on the gradual realization of machine substitution and extensive informatization, in September 2017, Jintian Copper launched the overall plan for intelligent manufacturing.
At present, the copper pipe factory has achieved most of the production data. In the workshop production control center, the production data, order progress and other information can be seen on the big screen at a glance.
At the end of 2020, the company's precision copper strip 5G production workshop was officially put into production.
Up to now, companies have piloted multiple application scenarios based on 5G communication technology, such as equipment data collection, instrument environment monitoring, and remote operation and maintenance.
Pan Jin, director of Jintian Copper Group, introduced that through intelligent transformation, the level of refined management of the enterprise has been continuously improved.
He gave an example: "Through comprehensive analysis of customer needs, process costs, equipment power consumption and other data, to optimize production scheduling and process execution, and scientifically guide peak-to-valley power operations, the comprehensive benefits have increased by more than 30% compared to the previous one. "
Official data confirms the changes brought about by smart transformation: as of the end of 2020, Ningbo has built a total of 100 digital workshops/smart factories above the city level, and 65 completed projects have promoted an average increase of 58.2% in enterprise production efficiency and average operating results. Reduced by 21.4%, energy consumption per unit output value has been reduced by 16.1% on average.
Motivation for transformation-
Large companies pay more attention to product quality improvement, the sooner they change, the more proactive they are
Judging from the results, the effect of smart transformation is generally gratifying.
When it comes to the motives of transformation and their own strengths, the thinking of large companies is quite the same.
"For us, the most important thing for intelligent manufacturing is to solve the problem of product consistency." Huang Xiaowei, president of Oaks Home Appliances Group, explained that home appliance manufacturing has realized mechanization and even automated production earlier, and belongs to a highly standardized industry.
However, due to the high value of a single product, any improvement in quality control will bring greater returns to the enterprise.
As a copper processing enterprise, Jintian Copper also regards strengthening quality control capabilities as an important goal of intelligent transformation.
In the copper pipe processing workshop, with the rapid rotation of the runner, a coil of copper pipe is produced.
However, occasionally a certain section of copper pipe is sprayed with black paint.
"There will inevitably be defects in the product production process. On the premise of meeting customer requirements, marking the defective parts can facilitate downstream processing and production." Pan Jin told reporters that through the on-line intelligent testing equipment, the intensity of manual testing is reduced while reducing the intensity of manual testing. , Which also greatly reduces the missed detection rate and false detection rate.
In some labor-intensive textile companies, intelligent transformation has also had a positive impact on the control of labor costs.
Whether it is to improve quality and efficiency, or to save energy and reduce consumption, the reporter learned during the interview that large enterprises have a strong desire for intelligent transformation and their advantages are obvious.
"The sooner we promote intelligent transformation, the more we can grasp the market initiative. This is determined by the strategic height of large companies. It is for this reason that we are willing to accept a longer return period." Huang Xiaowei introduced, since 2015, Oaks has successively With an investment of more than 3 billion yuan for intelligent transformation, the company's automation rate has reached 77%.
In addition, clear transformation goals are also an advantage for large companies.
Luo Yi, Information Director of Ningbo Xusheng Automotive Technology Co., Ltd., for example, said, “During the production of auto parts, we found that the original production system could not remotely grasp the specific conditions of the production site. Therefore, we need to use intelligent transformation to avoid the on-site You can always sense the fluctuations in the production process, thereby reducing risks and improving efficiency."
The transformation process-
There is a shortage of professional talents, and it takes time for workers to change their operating habits
Due to the numerous production lines and complex processes of large enterprises, intelligent transformation requires the effective matching and connection of multiple positions or even multiple production links.
But from the actual situation, in a period of time after the completion of the intelligent transformation, running-in is inevitable.
In April 2018, Youngor started a trial operation of the intelligent system on a coat production line, automatically transporting semi-finished garments in each process through the hanging line, stringing up the entire production process.
“There was a problem right after the operation,” said Xu Shili, the director of the Youngor Apparel Manufacturing Intelligent Manufacturing Research Institute. Less production schedule."
Why will it stop?
The technical department of the enterprise repeatedly communicated with the system service provider, and it took a long time to find the crux of the problem: the original production link did not produce enough data for the intelligent system to analyze and judge, and optimize production; the employees are not familiar with the new system and will not interfere with it manually. It led to the failure of the hanging line "strike".
Xu Shili said: "After continuous debugging and upgrading, this problem was not completely resolved until the end of that year."
In addition to the problems caused by this “insufficiency”, “the operating habits of workers are also difficult to change.” Huang Xiaowei recalled, “When companies first launched smart devices, some assembly lines required workers to scan codes and enter data for parts and components. It is difficult for people to get used to this way of operation at first, and it takes more than a year to fully adapt."
It is not uncommon for Youngor to encounter a situation, which is also a common problem faced by large manufacturing enterprises in the intelligent transformation-the shortage of intelligent manufacturing engineering and technical personnel.
"There are too few people who understand both technology and industry." Luo Yi said the pain points of the enterprise.
"Information technology personnel should be translators for business personnel, and transform the process, quality, monitoring and other operational experience into data information." Pan Jin explained that in the actual intelligent transformation process, information technology personnel may not understand the business. Business personnel may not understand information technology, and there is a barrier between the two.
During the interview, many companies said that the shortage of intelligent manufacturing engineering and technical personnel is related to the insufficient market supply of talents on the one hand, and the employment tendency of information technology talents on the other hand.
Li Na, deputy director of the Industrial Digitalization Division of Ningbo Economic and Information Bureau, found through interviews with companies: “The front line of factories is not attractive enough for young people, and IT talents are more inclined to work in Internet companies in big cities, and the professional setting of local colleges and universities There is a gap with the actual needs of enterprises, and enterprises still need to make more efforts to attract and train talents."
Transformation expectation——
Give full play to the leading role and drive the transformation of small and medium-sized enterprises
For large manufacturing companies, what is the focus of smart transformation in the next step?
"After the outbreak of the new crown pneumonia epidemic, smart manufacturing has provided many manufacturing companies with favorable conditions for resuming work and production, and it has also given them a certain opportunity in market competition." As a solution provider that specializes in providing smart manufacturing transformation services Xiao Yong, vice president of Ningbo Institute of Intelligent Manufacturing Technology, said that the next step should be to appropriately step out of the concept of "unmanned production" and explore the value of intelligent manufacturing in depth.
When it comes to the future expectations of intelligent manufacturing, "data" has become a key word for many companies.
Intelligent manufacturing has accumulated massive amounts of data on procurement, production, logistics, sales and other links for enterprises. How to make full use of these resources to better promote enterprise development?
Song Huasheng, a professor at Zhejiang University School of Economics, said, “Intelligent manufacturing requires companies to collect, analyze, and apply big data, and promote the integration of internal data and user behavior data around the product life cycle.”
"The role of data is to assist decision-making. Intelligent manufacturing is not to completely replace people, but to reduce the role of people and transform empirical production into digital decision-making." Feng Haoran, vice president of technology of Changzhi Technology Group Co., Ltd., said, for example Use data to study the relationship between process and cost, process and quality, so as to further optimize the production process.
So, for large-scale manufacturing enterprises with relatively high levels of intelligent manufacturing, how can they play a leading role in driving the intelligent transformation of small and medium-sized enterprises and help the supply chain industry chain upgrade?
In 2020, Ningbo issued the "Action Plan for the Intelligent Technology Transformation of Ningbo Manufacturing Enterprises (2020-2022)", proposing to encourage superior backbone enterprises with good basic conditions, strong innovation capabilities, and high levels of intelligence to develop 5G and artificial intelligence. New technologies such as intelligence and blockchain are integrated and innovated with smart manufacturing, and cultivate a group of smart manufacturing benchmark enterprises with obvious demonstration effects.
Support leading enterprises to build an industrial Internet platform for collaborative innovation of the industrial chain around the digital, networked, and intelligent needs of the upstream and downstream industrial chain ecosystem.
"Industrial chain competition is playing an increasingly prominent role in global competition, and large enterprises are the key to the industrial chain." Song Huasheng believes that large enterprises should play a dominant role, promote intelligent transformation in the form of industrial clusters and industrial ecology, and upgrade the entire industrial chain. The level of intelligent manufacturing.
"Using large enterprises as the node to radiate upstream and downstream, opening up the blocking points of all links will be an important part of the intelligent transformation in the future."
Our reporter Han Chunyao, Dou Hanyang and Bai Zhiyu