Intelligent manufacturing is a popular word nowadays, and there are many domestic enterprises doing intelligent manufacturing, such as Kaiyun United
Looking back at the policy, the field of intelligent manufacturing is the main direction of "Made in China 2025", and intelligent manufacturing is also a key area in the "13th Five-Year" National Science and Technology Innovation Plan. "Thirteen Five" national science and technology innovation plan, intelligent manufacturing is also a key area. Data show that in 2015, China's intelligent manufacturing output value of about 1 trillion yuan, 2020 is expected to exceed 3 trillion yuan, compound annual growth rate of about 20%. The establishment of this new area is intended to boost the growth of intelligent manufacturing.
How?
Big data-based PHM, or fault prediction and health management, is one of the key technologies for realizing industrial upgrading from a "manufacturing powerhouse" to a "manufacturing powerhouse.
In the last decade, the Internet of Things (IoT) has connected everything, and the sensors in IoT devices generate unprecedented amounts of data, but this data is not properly utilized, so how to bundle big data and intelligent maintenance has become a new challenge.
And big data-driven PHM, on the basis of making full use of the massive data of the unit, can realize feature extraction, fault warning, and fault pattern mining and matching of operating equipment through intelligent modeling technologies such as machine learning and deep learning, so as to predict the faults of a wide range of objects, from critical equipment to power grids.
Expanding, in the field of industrial production and manufacturing, as well as various types of dynamic or static operation systems such as airplanes, trains, roads, bridges, and other systems, by monitoring and analyzing the operating status data of complex equipment and components, it is possible to control the health of equipment in real time, accurately and comprehensively. If the operation of these devices can be full-dimensional monitoring and early warning, you can make accurate analysis and prediction before the equipment failure, in advance of the automatic issuance of repair and maintenance recommendations to ensure that each device is safe, reliable, and continuous operation, which is the equipment health management of industrial big data.
Heavy industry is the place for PHM?
Particularly in the petrochemical industry, metal smelting, equipment manufacturing and other heavy industry, the scale of the production unit is huge, belonging to the heavy asset production field, especially for the process-oriented manufacturing mode, must ensure that the entire production unit continues to operate and the production of safe and reliable. Therefore, equipment health management is more important in these fields, and it can be said that heavy industry is the place for PHM.
It is conceivable that in an intelligent factory, people, machines and resources will naturally communicate and collaborate with each other as in a social network, and production equipment and devices will be able to self-diagnose and maintain themselves; in the process of production operation, all kinds of equipment and devices will run in the best state and the most efficient way; before a failure occurs, the system will automatically perceive, automatically predict, and self-service maintenance to realize the cost, efficiency, and environmental protection, The system automatically senses, automatically predicts, and self-maintains before failures occur, achieving cost, efficiency, environmental protection, and great satisfaction of customers' individualized production needs.