The edge computing gateway industrial control application has edge side data collection capabilities, can provide intelligent computing capabilities across the edge side and the cloud, provide actionable decision feedback, and has the openness to connect to the decision execution system.
Edge computing gateway smart industrial applications
1. Intelligent equipment monitoring
Edge computing gateway supports more data transmission and processing, and ensures the real-time and reliability of transmission. Workshop equipment can be remotely controlled, used and operated in a timely manner, which can improve the ability to predict equipment failures, achieve predictive operation and maintenance, maximize equipment life and improve equipment utilization. 5G remote control equipment can achieve accurate and fast construction. Achieve the effects of improving work efficiency, saving costs, and reducing risk factors.
2.AI quality inspection
The AI quality inspection system uses advanced edge computing technology to sink AI applications into the production workshop, perform machine vision analysis close to the equipment, reduce the demand for network bandwidth for video transmission, and perform data acquisition, annotation, training, testing and Deploy, and then provide feedback on product category information, defect location, defect category and other inspection results according to product inspection requirements, achieving high-precision identification and analysis of industrial product appearance defects, shortening application response time, and improving business real-time performance.
3. Factory security
In the field of factory security, it is necessary to use edge computing to accurately locate personnel and link positioning information with real-time video, images and data transmission to ensure millisecond-level responses and prompts, provide guarantees for the effectiveness of early warnings, and prevent safety accidents. occur. At the same time, in order to long-term data storage for accident tracing, it is necessary to rely on the large bandwidth, real-time performance of edge computing and cloud mass storage to achieve these requirements.
4. Intelligent inspection
Traditional manual inspections have a heavy workload and are prone to missed inspections. Relying on 5G, AI and edge computing, intelligent inspection robots can replace human inspections. In the robot inspection scenario, the powerful big data processing capabilities of the cloud must be used to effectively extract and analyze equipment risk characteristic points, thereby forming an equipment inspection alarm model. Deploy robot management and DIAG system (diagnostic system) on the edge side, and transmit real-time high-definition inspection pictures, equipment information, environmental information, system interaction, etc. through the 5G network to determine whether the on-site products are consistent with the product information of the DIAG system to prevent omissions .
5. Intelligent control of logistics equipment
Within a smart factory, the scheduling algorithms for job collaboration among multiple AGVs are extremely complex, and complex environments and a large number of cross-regional jobs put forward higher requirements for communication stability and bandwidth. As the number of AGVs in the enterprise increases, cloud AGVs can better solve computing problems, and edge computing can provide cloud AGVs with highly reliable and low-latency communication conditions.