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

“In the global manufacturing strategy, Germany Industry 4.0, China Manufacturing 2025 and the US Industrial Internet are the strongest. The United States represents advanced technology, Germany represents advanced manufacturing, and the volume manufactured in China is the largest in the world. These three strategies have the greatest impact on the world.” Chen Ming, deputy dean of the Sino-German Engineering Institute of Tongji University and director of the Industry 4.0-Smart Factory Laboratory, said, “On our platform, there are only the first two, no industry. The Internet has also established this platform through the introduction of NI cooperation. So now the laboratory system has become very complete, can carry out a lot of work, play the respective characteristics of each strategy, and finally apply to solve the problem of China Manufacturing 2025. Contribution." Recently, Tongji University - National Instruments (NI) Industrial Internet Joint Experimental Center was officially unveiled at Tongji University's Jiading Campus. The experimental center was jointly built by Tongji University and NI, and is the first intelligent manufacturing laboratory in China with all the elements of Industry 4.0.
What is the Industrial Internet?
The Internet has created tremendous value in the consumer field. From the PC era to the mobile Internet era, the value created by the interconnection and interconnection has been rising, the Internet application has become the capital darling, the traditional manufacturing industry has been neglected, and the US manufacturing outflow phenomenon is very obvious. The vigilance of the US government. In 2013, US President Barack Obama made it clear that “to make the United States a new magnetic field for employment and manufacturing” and to ensure that the next manufacturing revolution takes place in the United States.
The US industry has begun to consider how to replicate the success of the Internet in the consumer sector to the industrial sector. Jeff Immelt, GE's chairman and chief executive, wrote that we ignore the enormous value that IT technology can create in the industrial world – just a productivity increase of 86,000 One billion dollars, which is twice the size of the future Internet consumer market. Obviously, the main driving force of the next wave of innovation will not come from areas such as on-demand services or video streaming."
He said: "Now, we need to put the same energy and enthusiasm into the industrial field and address the major challenges in medical care, infrastructure construction, electricity and transportation."
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. It is associated with 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 MIT Wireless Network Center.
Industrial Internet can be regarded as the US version of Industry 4.0, but it is still slightly different. According to Industrial Internet Chairman Joe Salvo, "Industry 4.0 transforms a traditional factory into a smart networked factory, another innovation in manufacturing. Industrial Internet It includes not only the manufacturing industry, but all the basic industries that need to analyze data and information, such as home care, transportation, electric energy, and water treatment, all of which are industrial Internet applications.
What is predictive maintenance?
The Industrial Internet Experimental Center of Tongji University and NI cooperated from predictive maintenance 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 nine test platforms including the status monitoring and predictive maintenance test platform (now expanded to 16), responsible for condition monitoring and predictive maintenance. The test platform members are IBM and NI.
Condition Monitoring (CM) refers to real-time monitoring of equipment operating status through sensors installed on the equipment. Predictive Maintenance (PM) analyzes the collected operational data in order to detect equipment performance degradation or failure at an early stage. Sign and give recommendations for actionable measures to notify line maintenance personnel to perform maintenance or troubleshooting to minimize downtime due to equipment failure and reduce equipment maintenance costs. In addition, the full monitoring of the equipment is also beneficial to equipment manufacturers to improve the equipment.
The advanced version of InsightCMEnterprise software released by NI at the unveiling ceremony is the CM/PM test platform solution. The solution faces the increasingly complex equipment monitoring problem and properly resolves the contradiction between test speed and test data volume. With InsightCM, users can gain in-depth understanding of the enterprise's asset equipment status for maintenance and operation of the aircraft. InsightCM combines with NI Industrial IoT technology platforms such as DIAdem and CompactRIO to conduct research in distributed sensor measurement, intelligent terminal processing, analysis and open communication, data management and other related fields.
Industrial big data without analysis and processing is worthless. Made in China 2025, it took 10 years to enter the ranks of manufacturing powerhouses. However, from the current situation of China's industrial development, the task of realizing China's manufacturing 2025 is very arduous. The current state of manufacturing in China is high energy consumption, low added value, and low-end in the value chain. The product manufacturing process is generally equivalent to “painting” and manufacturing relying on “manpower”, while the factors that reflect the characteristics of modern manufacturing 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 China Manufacturing 2025, talent training and conceptual change are the key. As the responsible teachers of the Tongji University Youth League Committee said, the mainstay of China's manufacturing 2025 is now in the university, but the phenomenon of university education and industry disconnection has a long history, so the university and the industry work closely together, so that college students can reach the industry most during the campus stage. Advanced technology and concepts are necessary. Dean Chen Ming also introduced that Tongji University Industry 4.0-Smart Factory Laboratory has been trained as a training pilot for the Ministry of Education Manufacturing and Industry 4.0. Several batches of trainees have been trained. Many industry associations have also commissioned Tongji to conduct relevant training. The university as a talent cultivation base must not only To do a good job in the training of basic knowledge, we must also keep the advanced nature, so that students can access the latest knowledge and concepts in the industry.
In terms of concept, intelligent manufacturing cannot be simply understood as informationization and automation. “Intelligent manufacturing, interconnection, and physical connection are different places between smart manufacturing and traditional manufacturing, but automation plus informationization is not equal to intelligent manufacturing,” Chen Ming said. “Automotive production lines have the highest degree of automation and the highest level of informatization. However, now the automobile production line is not an intelligent production line. Why? The automobile production line is a fixed production line. If a certain link in the middle is broken, all other links must be forced to stop work. Will the subsequent automated production line be a fixed production line? The dynamic production line, which directly controls each link from the top layer, must be more and more applications. Many companies are talking about smart manufacturing, but we have not understood this yet. Once we realize this, we can understand the interconnection. The meaning."
Tang Min, manager of NI China Marketing Department, agrees with this view. "Big data generated by device interconnection will not be worthwhile if it is not effectively analyzed and processed. Therefore, how to value industrial big data is the foundation of intelligent manufacturing. problem."