"Among the global manufacturing strategies, Germany's 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.” said Chen Ming, Deputy Dean of the Sino-German School of Engineering of Tongji University and Director of the Industry 4.0-Smart Factory Laboratory, “On our platform, there were only the first two, and no industrial Internet. Through the introduction of NI cooperation, this platform has also been established. So now this 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 applications to solve the problem of Made in China 2025 Contribution." Recently, the Tongji University-National Instruments (NI) Industrial Internet Joint Experimental Center was officially unveiled at the Jiading campus of Tongji University. The experimental center, jointly built by Tongji University and NI, is the first intelligent manufacturing laboratory with all elements of Industry 4.0 in China.

What is the Industrial Internet?

The Internet has created enormous value in the consumption field. From the PC era to the mobile Internet era, due to the continuous increase in the value created by interconnection, Internet applications have become the darling of capital, traditional manufacturing industries have been left out in the cold, and the outflow of American manufacturing is very obvious. alerted the U.S. government. US President Barack Obama made it clear in 2013 that he would "make the United States a magnetic field for new jobs and manufacturing" and ensure that the next manufacturing revolution occurs 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 General Electric, has written that we have overlooked the “great value that IT technology can create in the industrial world—86,000 in productivity gains alone. $100 million, which is twice the size of the future Internet consumer market. It is clear that the main driver of the next wave of innovation will not come from areas such as on-demand services or video streaming.”

"Now, we need to put the same energy and enthusiasm into the industrial sector, addressing major challenges in healthcare, infrastructure, power and transportation," he said.

Therefore, the Industrial Internet Consortium came into being. In this industry organization established in 2014, more than 200 members now include not only American companies such as General Electric, IBM, Intel and NI, but also Chinese companies including Huawei and Haier. With many well-known companies in Europe and Japan, as well as universities and scientific research institutions such as the University of California, Berkeley, and the MIT Wireless Network Center.

The Industrial Internet can be regarded as the American version of Industry 4.0, but it is still slightly different. According to Joe Salvo, Chairman of the Industrial Internet, "Industry 4.0 transforms traditional factories into intelligent networked factories, which is another innovation in manufacturing. Industrial Internet It not only includes manufacturing, but also all basic industries that need to analyze data and information, such as home care, transportation, power and energy, and water treatment industries, are applications of the Industrial Internet.”

What is predictive maintenance?

The Industrial Internet Experiment Center of 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 demonstrate the real application scenarios of the Industrial Internet, in February 2016, the Industrial Internet Alliance announced 9 test platforms including condition monitoring and predictive maintenance test platforms (now expanded to 16), responsible for condition monitoring and predictive maintenance The members of the test platform are IBM and NI.

Condition Monitoring (CM) refers to monitoring the operating status of equipment in real time through sensors installed on the equipment, while Predictive Maintenance (PM) analyzes the collected operating data in order to detect equipment performance degradation or failure at an early stage. Signs, and suggest actionable measures, notify line maintenance personnel for maintenance or troubleshooting, so as to minimize the loss of production downtime due to equipment failures and reduce equipment maintenance costs. In addition, the whole process monitoring of equipment is also beneficial to equipment manufacturers to improve equipment.

The InsightCMEnterprise software advanced version released by NI at the unveiling ceremony is the CM/PM test platform solution. This solution faces the increasingly complex equipment monitoring problem, and properly solves the contradiction between the test speed and the test data volume. With InsightCM, users can deeply grasp the status of the enterprise's assets and equipment, so as to maintain and operate the machine. Combining InsightCM with NI industrial IoT technology platforms such as DIAdem and CompactRIO, it can carry out research in related fields such as distributed sensor measurement, intelligent terminal processing, analysis and open communication, and data management.

Industrial big data is worthless without analytical processing

Made in China 2025 proposes to take ten years to enter the ranks of manufacturing powerhouses. However, judging from the status quo of my country's industrial development, the task of realizing Made in China 2025 is very arduous. The status quo of Chinese manufacturing is high energy consumption, low added value, and at the lower end of the value chain. The product manufacturing process is generally equivalent to "drawing" for design, and "manual" for manufacturing, while relying on digitization, automation, especially technological innovation, and other elements that reflect the characteristics of modern manufacturing are obviously insufficient, and there is a big gap compared with manufacturing powerhouses.

To achieve the goal of Made in China 2025, talent training and conceptual transformation are the keys. As the relevant 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 and industry are disconnected has a long history. Therefore, the university and industry are closely coordinated, so that college students can get in touch with the industry's most advanced students at the campus stage. Advanced technology and concepts are very necessary. Dean Chen Ming also introduced that Tongji University's Industry 4.0-Smart Factory Laboratory, as a training pilot for manufacturing and Industry 4.0 by the Ministry of Education, has trained several batches of students, and many industry associations have also entrusted Tongji to carry out relevant training. As a talent training base, universities not only need to Do a good job in the training of basic knowledge, and always maintain the advanced nature, so that students can come into contact with the latest knowledge and concepts of the industry.

In terms of concept, intelligent manufacturing cannot be simply understood as informatization and automation. "Intelligent manufacturing, interconnection, and interconnection between things and things are the differences between intelligent manufacturing and traditional manufacturing, but automation plus informatization does not equal intelligent manufacturing," Chen Ming said, "The automobile production line has the highest degree of automation and the highest degree of informatization. , but now the automobile production line is not an intelligent production line. Why? The automobile production line is a fixed production line. If a link in the middle is broken, all other links will be forced to stop work. Will the future automatic production line be a fixed production line? Dynamic production lines, where the top layer directly controls every link, there must be more and more applications like this. Many companies are talking about intelligent manufacturing, but they have not yet understood this point. Only when everyone realizes this point can they understand interconnection and interoperability. meaning."

Tang Min, manager of the NI China Marketing Department, also agrees with this view, "If the big data generated by the interconnection of equipment cannot be effectively analyzed and processed, it will be worthless. Therefore, how to value industrial big data is the foundation of intelligent manufacturing. question."