Because of the AI construction on the upper level of the industrial Internet of Things, the benefits will take some time to emerge, and it will not happen immediately, and it is not an urgent matter for the manufacturers, so most of the current investors are large-scale manufacturing industry, while the small and medium-sized ones are mainly based on the bottom edge operation.
At present, the establishment of the industrial Internet of Things in small and medium-sized enterprises, the predictive maintenance of manufacturing equipment and process testing are still two main functions. Because of the lack of early warning shutdown of equipment, the whole production line will be shut down, while the semi-finished products on-line will be scrapped, and the delivery delay will affect the goodwill. In the past, manual recording method was used for equipment maintenance, and personnel will maintain in accordance with time, except this way. It is possible that due to personnel negligence or laziness, failing to work regularly, the equipment may also fail before the maintenance time.
The predictive maintenance of equipment in the industrial Internet of Things can be divided into two categories. One is to design a reminder function directly on the management system to inform the relevant personnel of the maintenance time actively. The other is to detect the status of equipment by sensors. If there is an abnormality, AI will judge the possible situation according to the state frequency, and then do different processing, such as the vibration of motor detected by sensors. Maybe the axis is skewed, the system will judge the current state of the motor according to the magnitude and frequency of vibration. If it is likely to be damaged immediately, it will inform the equipment maintenance personnel to stop and replace. If there is no immediate danger, the motor will continue to operate, and record the motor's condition, so that the management personnel can decide the maintenance time, so that the production line can maintain stable operation efficiency.
Another main function of edge operation is process detection. According to the development of AI, image processing accounts for more than 70% of the applications, and it is also true in the industrial Internet of Things. In the past, people used to test the quality of products by eyes. Because people's eyes are easy to fatigue, the quality of detection will gradually decrease with the lengthening of working time. Moreover, the volume of some consumer products is smaller and smaller, the speed of production line is faster and faster, and the human eyes are hard to load. Now it has been replaced by machine vision.
At present, machine vision judgment speed is very fast and accuracy is getting higher and higher, but its operation mode is still fit for the design of mass manufacturing process. Its rapid and accurate identification can only be applied to a few types, and it still has not been captured in a small number of diversified or mixed-line production processes. AI can enable machine vision to have learning ability, and future equipment will be able to self-learn through algorithm. Learn, when encountering different product types or defects, you can judge independently, without having to reset and adjust the discriminant mode by the managers.
TAICENN, is a leading global solution provider of Embedded Box PC, Touch panel PC and industrial monitor, which are designed specifically for systems and applications that require excellent performance, high-level reliability and stability, long supply period and supports.
Thank you for your support and cooperation!
For product: email@example.com
For technical: firstname.lastname@example.org