Industry big data value is the basic problem of intelligent manufacturing
"In the global manufacturing strategy, the German industry 4, China made 2025 and the United States industrial Internet, the three is the strongest. The United States represents the advanced technology, Germany represents the advanced manufacturing, the volume of China's manufacturing is the world's largest. These three strategies, the greatest impact on the world." Vice president of Sino German Engineering Institute of Tongji University, industrial 4.0- intelligent factory laboratory director Chen Ming said, in our platform, the original only the first two, there is no industrial internet. Through the introduction of NI cooperation, the platform is also built up. So now the laboratory system has become very complete, can carry out a lot of work, play the characteristics of each strategy, and ultimately contribute to the application of China's manufacturing 2025 problems." Recently, Tongji University - National Instruments (NI) industrial Internet joint experimental center at the Jiading campus of the Tongji University officially inaugurated. The experimental center jointly built by the Tongji University and the NI, is the first of the 4 industrial elements of the industry's first intelligent manufacturing laboratory.
What is the industrial Internet?
The Internet has created enormous value in the field of consumption, from the PC era to the era of mobile Internet, the interconnection value rising, Internet application has become the capital darling of the traditional manufacturing industry is not popular, American manufacturing outflow phenomenon is very obvious, this caused the U.S. government's alert. US President Barack Obama made it clear in 2013 that "to make the United States a magnetic field for new jobs and manufacturing," to ensure that the next manufacturing revolution took place in the United States.
The US industry began to consider how to replicate the success of the Internet in the field of consumption to the industrial field. Ge chairman and chief executive officer Jeff Immelt (JeffImmelt) wrote that we ignore the huge value of IT technology can create in the industrial world -- just a productivity improvement can bring $8 trillion and 600 billion, two times the equivalent to the size of the future Internet consumer market. It is clear that the main driving force of the next wave of innovation will not come from the field of demand services or video streaming."
He said: "now, we need to put the same energy and enthusiasm into the industrial field, committed to solving the major challenges in health care, infrastructure construction, electricity and transportation, etc.."
Therefore, the Internet Industry Alliance (IndustrialInternetConsortium) came into being in this industry organization established in 2014, now more than and 200 members not only have general electric, IBM, Intel and NI and other American companies, many well-known companies including HUAWEI, Haier, and Chinese company in Europe, Japan, and University of California at Berkeley, Massachusetts Institute of Technology, University of wireless network center with the scientific research institutions.
The Internet industry can be seen as the American version of the 4 industry, but still slightly different, according to the Internet industry chairman Zhou Si Zhe (JoeSalvo) said, "4 will be the transformation of traditional industrial factory for intelligent network factory, is an innovation in the manufacturing industry. The Internet industry includes not only the manufacturing industry, all the need for basic industry analysis of data and information, such as home care, transportation, energy and water treatment industries, are the applications of the Internet industry".
What is predictive maintenance?
Tongji University and NI cooperation of industrial Internet experimental center from predictive maintenance, and gradually expand to the various aspects of intelligent manufacturing, then what is predictive maintenance?
In order to show the real application scenarios of the Internet industry, the Internet industry alliance released February 2016 includes status monitoring and predictive maintenance test platform, 9 test platform (now has expanded to 16), responsible for the condition monitoring and predictive maintenance to test platform is IBM and NI.
Condition monitoring (CM) refers to the running state of real-time monitoring equipment through sensors installed on the device, predictive maintenance (PM) is the operation of the data collected for analysis, in order to find the early equipment performance degradation or failure signs, and gives the suggestions of measures implementation, inform production line maintenance personnel in maintenance or troubleshooting, thereby minimizing production losses caused by equipment failure, and reduce equipment maintenance cost. In addition, the whole process of monitoring equipment is also conducive to equipment manufacturers to improve equipment.
NI released at the opening ceremony of the InsightCMEnterprise software is the advanced version, CM/PM testing platform solutions. The solution to the complicated problems of the equipment monitoring, to properly resolve the contradictions, test speed and the amount of test data with the help of InsightCM, the user can grasp the assets of the enterprise, in order to carry out the maintenance and operation of the flight. InsightCM and CompactRIO, NI and other DIAdem industrial networking technology platform, can carry out the distributed sensor measurement, intelligent terminal processing, analysis and open communication, data management and other related fields.
Industrial data processing have not worth a hair
Made in China ten to 2025 years, into the ranks of manufacturing power. But from the current situation of China's industrial development, the realization of China's manufacturing 2025 of the task is very arduous. The status quo of China's manufacturing is high energy consumption, low added value, in the low end of the value chain. The manufacturing process is generally designed as "drawing", rely on the manufacturing "hands", and rely on the digitization and automation especially elements of technological innovation embodied the modern manufacturing feature is obviously insufficient, there is a big gap compared with manufacturing power.