As an indispensable device for automated smart devices, sensors will welcome new development opportunities as downstream demand grows and industrial application speeds increase. The relevant agencies expect that in the next five years, the compound annual growth rate of the sensor market in China will reach about 30%, and the market scale is expected to continue to expand. At present, in the Pearl River Delta cities represented by Foshan and Dongguan, a new industrial revolution is taking place rapidly. This year, Foshan proposed to build a pilot city of “Internet + smart manufacturing†in China and develop new manufacturing models such as cloud manufacturing based on the industrial Internet. Among these, it is inseparable from the transformation of sensors to intelligent systems.
Collecting data from layout sensors, visualizing data, analyzing data using software, and finally using data to make decisions are the four-step big data technology path of the Industrial Internet.
Nowadays, more and more companies collect data through sensors and create new business models. In the layout of industrial Internet of things, domestic enterprises cooperate with excellent domestic and foreign manufacturers to help enterprises optimize decision-making and reduce costs by arranging machine sensors and collecting analysis data.
Take the United States as an example, the U.S. government has been laying out long-term basic innovation research. In 2012, the United States began to build 45 manufacturing innovation institutes throughout the United States, focusing on areas such as additive manufacturing. In 2014, the United States increased its investment by more than 300 million U.S. dollars to support three key technologies: advanced materials, advanced sensors, and digital manufacturing.
More and more companies collect analytical data through sensors
In addition, the Industrial Internet runs through multiple U.S. industry chains. For example, machinery leasing companies can increase their turnover by 20% based on sensors detecting machine usage. Networking of machines by machine manufacturers can predict failures and increase production efficiency.
For example, according to Boeing plant personnel in the United States, Boeing aircraft are equipped with thousands of sensors. Based on the collection and analysis of the massive data during the voyage, the aircraft can determine what problems will occur on the second day of the route, and check and replace parts before takeoff to reduce the risk.
Collecting data from layout sensors, visualizing data, analyzing data using software, and finally using data to make decisions are the four-step big data technology path of the Industrial Internet.
Nowadays, more and more companies collect data through sensors and create new business models. In the layout of industrial Internet of things, domestic enterprises cooperate with excellent domestic and foreign manufacturers to help enterprises optimize decision-making and reduce costs by arranging machine sensors and collecting analysis data.
Take the United States as an example, the U.S. government has been laying out long-term basic innovation research. In 2012, the United States began to build 45 manufacturing innovation institutes throughout the United States, focusing on areas such as additive manufacturing. In 2014, the United States increased its investment by more than 300 million U.S. dollars to support three key technologies: advanced materials, advanced sensors, and digital manufacturing.
More and more companies collect analytical data through sensors
In addition, the Industrial Internet runs through multiple U.S. industry chains. For example, machinery leasing companies can increase their turnover by 20% based on sensors detecting machine usage. Networking of machines by machine manufacturers can predict failures and increase production efficiency.
For example, according to Boeing plant personnel in the United States, Boeing aircraft are equipped with thousands of sensors. Based on the collection and analysis of the massive data during the voyage, the aircraft can determine what problems will occur on the second day of the route, and check and replace parts before takeoff to reduce the risk.
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