Since the advent of PLC in 1969, automation technology has gradually taken a firm foothold in the field of manufacturing. Now it is the core framework of global manufacturing system. Because of the stability of manufacturing system, the acceptance speed of new technology and new architecture has been slow. However, the rapid changes in the consumer market in recent years have brought severe challenges to global manufacturing industry, and the introduction of intelligent architecture has become necessary for the sustainable operation of the industry. Strategies, and in the new generation of manufacturing systems, the industrial Internet of Things will not only become the core architecture, but also with AI (artificial intelligence) to implement the vision of intelligence.
All field applications of the Internet of Things have the same architecture. They are three-tier architectures composed of sensors, communication networks and cloud management platforms. The data of devices are captured by sensors, then transmitted to the upper cloud platform through communication networks for storage and operation. Finally, the analyzed data are used as a decision-making reference for system operation. In the overall architecture, AI was built in the past. The upper cloud platform, through powerful machine learning algorithm, analyses the massive data returned by the terminal sensing layer.
However, machine learning algorithm needs a certain amount of computing time, and its purpose is mostly to solve the long-term problems similar to process scheduling optimization in manufacturing industry. Real-time problems encountered in manufacturing process and feedback of control instructions will be slow. In recent two years, the concept of edge computing has emerged, which has become the best solution to the real-time problems of industrial Internet of Things.
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