Recently, heavyweight documents have been issued intensively, and the real economy has been raised to an unprecedented strategic height.
The Fifth Plenary Session of the 19th Central Committee proposed to adhere to the focus of economic development on the real economy, firmly build a strong manufacturing country, a strong quality country, a strong network country, and a digital China, promote the upgrading of industrial foundations and modernization of industrial chains, and improve economic quality, efficiency, and core competitiveness.
It can be seen that the transformation and upgrading of the manufacturing industry is imperative, and intelligent manufacturing has become a new trend of the times.
In addition to China, Germany's Industry 4.0 strategy, the United States' Industrial Internet program, and Japan's Super Intelligent Society 5.0 blueprint are all attempting to move towards intelligent manufacturing. Advanced technologies such as artificial intelligence, the Internet of Things, big data, cloud computing, and 5G are revolutionizing traditional industries under the name of Industry 4.0.
Current situation of China's manufacturing industry
According to World Bank data, in 2010, China's manufacturing added value surpassed that of the United States for the first time, becoming the world's largest manufacturing country, and has remained the world's number one for several consecutive years since then. However, McKinsey's data shows that China's manufacturing industry relies more on labor-intensive industries, and its independent innovation ability is relatively weak, putting it in an awkward situation of being "big but not strong".
Xie Qingshan, Industry Sales Manager of Intel's Asia Pacific IoT Business Unit in China, analyzed that compared to other countries, China's manufacturing industry presents two characteristics: a high proportion of small and medium-sized enterprises, and a wide coverage of the industry. Therefore, the core problem that China's intelligent manufacturing needs to solve is how to help a large number of small and medium-sized enterprises complete the digitalization and informatization upgrading of manufacturing processes. "To achieve the goal of transforming from a manufacturing powerhouse to a manufacturing powerhouse, we can only strengthen research and development, and transform the manufacturing industry with the world's latest high-tech. There is no shortcut."
Wang Jin, Chief Intelligent Manufacturing Expert of TCL Gechuang Dongzhi Technology Co., Ltd., believes that the competitiveness of China's manufacturing industry in the international market is constantly increasing, and the transformation of the manufacturing industry is in a critical period. However, the proportion of low-end manufacturing industry is still high. At the same time, low-end manufacturing enterprises are also facing difficulties in recruitment and employment due to low technical content and dry content. Assisting manufacturing enterprises in intelligent transformation, whether from the perspective of enterprises, countries, or the global trend, is a necessary and only path.
In the era of the Internet, user needs are becoming increasingly diverse and customized, and enterprise orders are showing a trend of miniaturization and fragmentation. Introducing and applying intelligent manufacturing system solutions has become an important focus for enterprises to meet the development needs of the new era.
Intelligent manufacturing not only brings new technologies to enterprises, but also new productivity, production relations, and production methods. Its ultimate goal is to improve the ability of enterprises to actively adapt to market changes.
In Xie Qingshan's view, the realization of ideal intelligent manufacturing requires joint investment from the entire industry chain, support from infrastructure, and joint cooperation between upstream and downstream.
While transforming the consumer service industry, internet technology is rapidly and firmly entering the industrial sector. Every Chinese person has enjoyed the convenience brought by internet technology, from Taobao, WeChat, takeout to online education. In the future, the manufacturing industry will also benefit greatly from it.
Xie Qingshan believes that the rapid development of internet technology has also brought us a huge dividend, which is that the cost of high-performance computing chips and the related industrial chain, including the construction and use costs of internet communication systems and artificial intelligence technology, are rapidly decreasing. These factors have laid a solid foundation for the transformation of manufacturing towards digitalization and intelligence.
Intelligent manufacturing is unstoppable
In recent years, a mainstream view has been that China's demographic dividend is disappearing, coupled with the intensification of aging issues, leading to survival difficulties for labor-intensive traditional manufacturing industries.
Wang Jin believes that "machines replacing humans" represented by automation first solve the problems of human beings in terms of material and energy, helping people work; Secondly, the introduction of digitalization and intelligence, represented by intelligent manufacturing, has solved the difficulties of human decision-making and helped people make decisions. So, humans can be liberated and do more creative work.
Statistical data shows that in traditional processing and assembly enterprises, an average of 500 errors occur for every one million manual operations, while the probability of robots making this error is only 11.5 errors per million.
Give a typical case. Audi has 2500 automatic robots on its production line at the Kassum factory. Mainly used to perform specific tasks required for assembling Audi cars. 900 of these robots are equipped with welding guns, and their work includes spot welding to fix metal parts together. Each car has approximately 5000 welding points. If about 1000 cars are assembled every day, there will be over 5 million welding operations per production day.
In order to ensure welding quality, it is reasonable to conduct quality control inspections on all welding points. However, it is impossible to rely on manual inspection of 5 million solder joints, so in the past, industry standard sampling methods could only accurately detect about one thousandth of them, and quality hazards were inevitable.
In response to this issue, Intel collaborated with Audi to use Intel's Industrial Edge Insight Platform (EII) to accelerate the creation of algorithms and conduct predictive analysis and modeling. This solution extracts data from all monitoring of the welding gun controller and directly compares and analyzes it with historical actual detection data provided by Audi on the edge of the site, in order to train its accuracy in artificial intelligence.
The application of these data operations and analysis results can not only help control engineers and operators improve the quality control of spot welding, but also be used in other application scenarios involving robots and controllers, such as riveting, bonding, and painting. And the system will remind technical personnel when predicting changes with potential faults, so as to minimize or eliminate the total number of errors as much as possible.
After cooperating with Intel, Audi's welding quality inspection rate on the production line has changed from one car per day to 100% complete inspection, greatly reducing potential quality hazards, lowering costs, and increasing profits.
Machines can both work and learn, which has sparked another panic about whether humans will be replaced by machines in the future. Daniela Ruth, director of the Computer Science and AI Laboratory at the Massachusetts Institute of Technology, believes that the current theme of scientific exploration should be the methods of human machine collaboration, rather than the panic of machines replacing humans.
From the perspective of managers, Xie Qingshan believes that if simple, mechanical, and repetitive work is handed over to machines and every employee is engaged in exploratory work, it will greatly enhance the overall competitiveness of the enterprise.
In fact, the ultimate strategic decision of a company cannot be made by machines, but must be made by people. The ultimate goal of machine automation is to serve people and meet their needs.
Digital transformation and upgrading path
It is an undeniable fact that the manufacturing industry needs to undergo transformation and upgrading. But how should the crucial step be taken?
Wang Jin believes that manufacturing enterprise managers should have the correct concept of digital transformation. Often, managers first have the correct concept and firm belief that digitization is a necessary path for enterprise transformation, and industrial internet is an effective means. Then, through overall planning and step-by-step implementation plans, they can improve overall production efficiency.Some viewpoints also believe that intelligent manufacturing cannot rely solely on the spontaneity and consciousness of enterprises, but should form an industrial chain covering the entire process of research and development, design, production, circulation, delivery, and after-sales service under the guidance of technology.
This year marks Intel's 35th birthday in China. Xie Qingshan quoted an ancient saying, "Water works for all things without competition." He believes that Intel's products are like water, penetrating into thousands of households, allowing every enterprise to develop better.
As is well known, welding is an indispensable process in production and manufacturing, from the assembly of ships and airplanes to the manufacturing of circuit boards, all require deep participation in the welding process. Precision welding has very strict technical requirements, and only skilled senior technicians can be competent. The training of such technicians requires long-term repetition of a single operation, and the long-term accumulation of risks during the welding process may bring significant harm to the physical health of workers. Therefore, this job is considered to have low happiness, which has led to an increasing number of young people unwilling to engage in this job.
Therefore, in the industrial welding process, welding execution operations shift from "human" to "machine", and achieving automated and intelligent welding becomes crucial. Compared to humans, machines have higher welding accuracy and can work continuously for 7 * 24 hours, providing high-speed and stable welding capabilities, significantly improving welding efficiency and saving labor costs. In addition, automated welding can avoid human defects such as negligence and fatigue, and improve welding quality.
Karl Marx once said that there is no smooth road in science, only those who are not afraid of climbing steep mountain paths with labor have the hope of reaching the pinnacle of glory.
Nowadays, the manufacturing industry is ushering in a spring of high-quality development.
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