"Among the global manufacturing strategies, German industry 4.0, made in China 2025 and the industrial Internet of the United States are the strongest. The United States represents advanced technology, Germany represents advanced manufacturing, and China's manufacturing volume is the largest in the world. These three strategies have the greatest impact on the world. " Chen Ming, vice president of the Sino German engineering school of Tongji University and director of the industrial 4.0-intelligent factory laboratory, said, "on our platform, there were only the first two, and there was no industrial Internet. Through the introduction of Ni cooperation, the platform is also established. So now the laboratory system has become very complete and can carry out a lot of work, give play to the characteristics of each strategy, and finally make application contribution to solve the problem of made in China 2025. " Recently, Tongji University National Instrument (Ni) industrial Internet joint experimental center was officially opened in Jiading campus of Tongji University. The experimental center, jointly built by Tongji University and Ni, is the first intelligent manufacturing laboratory with the full elements of industry 4.0 in China.
What is the industrial Internet?
The Internet has created great value in the field of consumption. From the PC era to the mobile Internet era, due to the rising value created by interconnection, Internet applications have become the darling of capital, while the traditional manufacturing industry is quite neglected. The outflow of American manufacturing industry is very obvious, which has aroused the vigilance of the US government. In 2013, U.S. President Barack Obama made it clear that "let the United States become a magnetic field for new jobs and manufacturing industries", and to ensure that the next manufacturing revolution takes place in the United States.
American industry began to consider how to replicate the success of the Internet in the consumer sector to the industrial sector. Jeff Immelt, chairman and chief executive of Ge, once wrote that we have ignored the great value that it technology "can create in the industrial world - productivity improvement alone can bring us $8.6 trillion, which is twice the size of the future Internet consumer market. Clearly, the main driver of the next wave of innovation will not come from areas like on-demand services or video streaming. "
"Now, we need to put the same energy and enthusiasm into the industrial sector to address the major challenges of health care, infrastructure, electricity and transportation," he said
Therefore, the industrial Internet consortium came into being. In this industry organization established in 2014, more than 200 members are not only American companies such as general electric, IBM, Intel and Ni, but also Chinese companies including Huawei and Haier, as well as many well-known companies in Europe and Japan, as well as the University of California, Berkeley and MIT wireless Network center and other universities and scientific research institutions.
Industrial Internet can be regarded as the US version of industry 4.0, but it is still slightly different. According to Joe alvo, chairman of industrial Internet, "industry 4.0 transforms traditional factories into intelligent networked factories, which is another innovation of manufacturing industry. The industrial Internet includes not only the manufacturing industry, but also all the basic industries that need to analyze data and information, such as home care, transportation, power and energy, and water treatment, etc., which are the application occasions of industrial Internet.
What is predictive maintenance?
The industrial Internet experimental center cooperated by Tongji University and Ni started from predictive maintenance and gradually expanded to all aspects of intelligent manufacturing. So what is predictive maintenance?
In order to show the real application scenarios of the industrial Internet, in February 2016, the industrial Internet Alliance announced nine test platforms including the condition monitoring and predictive maintenance test platform (now it has been expanded to 16). The members responsible for the condition monitoring and predictive maintenance test platform are IBM and Ni.
Condition monitoring (CM) refers to real-time monitoring of equipment operation status through sensors installed on the equipment, while predictive maintenance (PM) analyzes the collected operation data, so as to find out the signs of equipment performance degradation or failure in the early stage, and gives feasible treatment suggestions, and informs the production line maintenance personnel to carry out maintenance or troubleshooting, so as to maximize the limit Reduce the production loss caused by equipment failure, and reduce the cost of equipment maintenance. In addition, the whole process monitoring of equipment is also conducive to equipment manufacturers to improve equipment.

At the unveiling ceremony, Ni released the advanced version of insightcm enterprise software, which is the solution of cm / PM test platform. The solution directly faces the increasingly complex equipment monitoring problems, and properly solves the contradiction between test speed and test data volume. With insightcm, users can deeply grasp the assets and equipment status of the enterprise, so as to maintain and operate the aircraft stands. Insightcm can carry out research on distributed sensor measurement, intelligent terminal processing, analysis and open communication, data management and other related fields by combining with Ni industrial Internet of things technology platforms such as diadem and compactrio.
Industrial big data without analysis and processing is worthless
Made in China 2025 proposes to step into the ranks of manufacturing powers in 10 years. But from the current situation of China's industrial development, the task of realizing made in China 2025 is very arduous. The status quo of manufacturing in China is high energy consumption, low added value and low value chain. In general, the product manufacturing process is that design is equivalent to "drawing", and manufacturing relies on "human resources". However, the elements reflecting modern manufacturing characteristics, such as relying on digitization, automation, especially technological innovation, are obviously insufficient, and there is a big gap compared with the manufacturing power.
To achieve the goal of made in China 2025, talent training and concept change are the key. As the teacher in charge of the Youth League Committee of Tongji University said, the mainstay of made in China 2025 is now in the University, but the phenomenon that university education is divorced from industry has a long history. Therefore, it is very necessary for the University and industry to cooperate closely to let college students have access to the most advanced technology and concepts in the industry at the campus stage. President Chen Ming also introduced that the industrial 4.0- intelligent factory laboratory of Tongji University, as the pilot of the Ministry of education's manufacturing and industry 4 training, has trained several batches of students. Many trade associations have commissioned Tongji to carry out relevant training. As a base for personnel training, universities should not only do well in training basic knowledge, but also keep the advanced nature, so that students can get in touch with the latest knowledge and outlook in the industry. Read.
In terms of concept, intelligent manufacturing can not be simply understood as informatization and automation. "Intelligent manufacturing, interconnection and material connectivity are the differences between intelligent manufacturing and traditional manufacturing. However, automation and informatization are not equal to intelligent manufacturing," said Chen Ming. "Automobile production lines have the highest degree of automation and informatization, but now automobile production lines are not intelligent production lines. Why? Automobile production line is a fixed production line. If one of the intermediate links breaks down, all other links will be forced to stop work. Will the future automatic production line be a fixed production line? Using dynamic production line, each link is directly controlled by the top level, so the application will be more and more. Many enterprises are talking about intelligent manufacturing, but they have not yet understood this point. Only when we realize this can we understand the significance of interconnection. "
Tang Min, manager of Ni's China marketing department, also agrees with this view, "if big data generated by equipment interconnection cannot be effectively analyzed and processed, it will be worthless. Therefore, how to value industrial big data is the fundamental problem of intelligent manufacturing. "