The value of industrial big data is the fundamental problem of intelligent manufacturing

"Among global manufacturing strategies, Germany's Industry 4.0, Made in China 2025 and America's Industrial Internet are the strongest. The United States represents advanced technology, Germany represents advanced manufacturing, and China is the largest manufacturer in the world. These are the three strategies that will have the biggest global impact." Chen Ming, deputy dean of the Sino-German School of Engineering at Tongji University and director of the Industry 4.0-Smart Factory Lab, said, "On our platform, we used to have only the first two and no industrial Internet. By introducing NI cooperation, this platform is also established. So now the lab system is very complete and can carry out a lot of work, give play to the characteristics of each strategy, and ultimately contribute to the application of the Made in China 2025 problem." Recently, Tongji University-National Instruments (NI) Industrial Internet Joint Experimental Center was officially inaugurated 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?

Internet has created huge value in the field of consumption. From the PC era to the mobile Internet era, due to the rising value created by interconnection, Internet application has become the darling of capital, while traditional manufacturing industry has been neglected. The outflow of American manufacturing industry is very obvious, which has aroused the alarm of the American government. In 2013, US President Barack Obama made it clear that he would "make America a magnet for new jobs and manufacturing" and ensure that the next manufacturing revolution takes place in the US.

American industry is beginning to think about how to replicate the success of the Internet in the consumer world in the industrial world. JeffImmelt, chairman and chief executive of General Electric, has written that we are ignoring the enormous value that IT "can create in the industrial world -- $8.6tn in productivity gains alone, twice the size of the future Internet consumer market. It is clear that the main drivers of the next wave of innovation will not come from areas like on-demand services or video streaming."

"Now we need to apply the same energy and enthusiasm to industry, to tackling the big challenges in healthcare, infrastructure, electricity and transportation," he said.

Internet industry alliance (IndustrialInternetConsortium) arises at the historic moment, therefore, in this industry group was founded in 2014, is now more than 200 members not only have ge, IBM, Intel with American companies such as NI, It also includes Chinese companies such as Huawei and Haier and many well-known companies in Europe and Japan, as well as universities and research institutions such as the University of California at Berkeley and the Massachusetts Institute of Technology Wireless Network Center.

Industrial Internet can be seen as the US version of Industry 4.0, but there is a slight difference, according to the chairman of Industrial Internet (JoeSalvo), "Industry 4.0 transformed traditional factories into smart networked factories, is another innovation in manufacturing. The industrial Internet not only includes manufacturing, but also all the basic industries that need to analyze data and information, such as home care, transportation, power energy and water treatment, etc."

What is predictive maintenance?

The Industrial Internet Experimental Center of Tongji University and NI cooperation starts from predictive maintenance and gradually expands to all links of intelligent manufacturing. Then what is predictive maintenance?

In order to demonstrate the real world of the Industrial Internet, in February 2016 the Industrial Internet Alliance announced nine (now 16) test platforms, including the health monitoring and predictive maintenance test platform. IBM and NI are responsible for the health monitoring and predictive maintenance test platform.

Condition monitoring (CM) is to monitor the running status of equipment in real time through the sensor installed on the equipment. Predictive maintenance (PM) analyzes the collected running data, so as to find the signs of equipment performance deterioration or failure in early stage, and give suggestions on actionable handling measures to inform production line maintenance personnel for maintenance or troubleshooting. In this way, the production loss caused by equipment failure can be minimized and the maintenance cost of equipment can be reduced. In addition, the whole-process monitoring of equipment is also conducive to equipment manufacturers to improve equipment.

At the unveiling ceremony, NI launched InsightCMEnterprise software Advanced Edition, which is the CM/PM test platform solution. The solution faces the increasingly complex device monitoring problem and properly solves the contradiction between test speed and test data volume. With InsightCM, users can deeply understand the status of enterprise assets and equipment for maintenance and operation. InsightCM, combined with NI industrial iot technology platforms such as DIAdem and CompactRIO, can conduct research in related fields such as distributed sensor measurement, intelligent terminal processing, analysis and open communication, and data management.

Industrial big data without analytical processing is worthless
Made in China 2025 has proposed that China will become a manufacturing powerhouse in 10 years. But judging from the current situation of China's industrial development, the task to achieve Made in China 2025 is very difficult. The current situation of Chinese manufacturing is high energy consumption, low added value and at the lower end of the value chain. In the process of product manufacturing, design is equivalent to "drawing", manufacturing depends on "human hands", and rely on digitalization, automation, especially technological innovation and other elements reflecting the characteristics of modern manufacturing are obviously insufficient, and there is a big gap compared with the manufacturing power.

To achieve the goal of Made in China 2025, talent cultivation and concept change are key. As the relevant teacher in charge of the Youth League Committee of Tongji University said, the pillars of Made in China 2025 are now in universities, but the phenomenon of disconnection between university education and industry has been going on for a long time. Therefore, it is very necessary for universities to cooperate closely with industry, so that college students can have access to advanced technologies and concepts in the industry during the campus period. Chen Ming also introduced that as a pilot training program for manufacturing and Industry 4.0 of the Ministry of Education, the Industrial 4.0-Intelligent Factory Laboratory of Tongji University has trained several groups of students, and many industry associations have entrusted Tongji to conduct relevant training. As a talent cultivation base, universities should not only train basic knowledge, but also maintain their advanced nature forever. To expose students to the latest knowledge and concepts in the industry.

In terms of concept, intelligent manufacturing can not be simply understood as information and automation. "Intelligent manufacturing, interconnection, connection between things, this is the difference between intelligent manufacturing and traditional manufacturing, but automation and information does not equal intelligent manufacturing," Chen Ming said. "The auto production line has the highest degree of automation, the highest degree of information, but now the auto production line is not intelligent production line. Why? An automobile production line is a fixed production line. If a link breaks down in the middle, all other links will be forced to shut down. Will the future automatic production line be a fixed production line? The use of dynamic production lines, by the top layer of direct control of each link, such applications must be more and more. A lot of companies are talking about smart manufacturing, but they don't understand it yet. When people realize this, they will understand the meaning of connectivity."

Tang Min, marketing manager of NI China, agrees, "Big data generated by device connectivity is worthless if it is not analyzed and processed effectively. Therefore, how to value industrial big data is the fundamental problem of intelligent manufacturing."