In industrial production, the accuracy of the assembly process directly affects product quality. WeLinkirt's SkyVision platform provides an effective way to solve the problem of detecting omitted steps in the assembly process.
User Scenario: A leading industrial manufacturing company's product assembly line is mainly responsible for the assembly process of complex mechanical equipment. In this process, the product consists of multiple components, and the detection object is whether each assembly step is performed according to the standard operating procedure (SOP). Once there is an omitted step, the product performance may decline or even the product may not work properly.
Pain Points: In the traditional detection of the assembly process, manual inspection is mainly relied on, but it has great limitations. On the one hand, the missed-detection rate of manual inspection is as high as 12%, making it difficult to ensure 100% full inspection, and some subtle omitted steps are easily ignored. On the other hand, the false-alarm rate of manual inspection is about 15%, increasing the unnecessary re-inspection workload. At the same time, the labor cost is high, and when the production line is changed, the inspectors need to be retrained, and the change-over time is as long as 30 minutes, seriously affecting the production efficiency. In addition, with the development of technologies such as intelligent security, video surveillance, and behavior recognition, the traditional manual detection method can no longer meet the industry's requirements for precise monitoring and compliance of the production process.
Technical Principle
The SkyVision zero-code video surveillance AI platform uses advanced computer vision algorithms and deep-learning technologies. Based on the semantic understanding ability of the DaoAI World model, it can accurately identify and analyze various elements in the assembly scene. By obtaining real-time video images from the surveillance cameras deployed on - site, the platform uses a convolutional neural network (CNN) to extract and classify features of the assembly actions and component states in the images.
- The model can learn the standard features of each assembly step. When there is a situation that does not meet the standard, such as a component not being installed or the assembly sequence being wrong, the platform can quickly identify it as an omitted-step event.
- The edge box of the platform has real-time computing power, which can process and analyze video data locally, realizing 100% local data storage without leaving the site, ensuring data security and improving detection efficiency.
- Using zero-code programming technology, on - site personnel can complete the training of their own models within hours without professional programming knowledge, greatly shortening the model deployment time.
WeLinkirt Solution and Product
Centered around the SkyVision zero-code video surveillance AI platform, WeLinkirt provides a complete solution for detecting omitted steps in the assembly process. First, high-definition surveillance cameras are deployed at key positions on the production line to ensure that every detail of the assembly process can be fully captured. Then, using the zero-code function of the SkyVision platform, on - site engineers can complete the training of their own detection models within hours according to the actual SOP process. The behavior/event recognition function of the platform can monitor every action in the assembly process in real-time. Once an omitted step is detected, the edge box immediately issues a real-time alarm. At the same time, combined with the semantic understanding ability of the DaoAI World model, the platform can generalize across different assembly scenarios and product types, improving the accuracy and universality of detection. In addition, WeLinkirt's DaoAI AI AOI software system and DaoAI 2D/3D AI AOI equipment can be used as an auxiliary to further improve the detection accuracy of components.
The SkyVision platform provides strong support for the quality assurance of industrial assembly processes with its efficient and accurate detection capabilities.
Quantitative Results: After using the SkyVision platform, the detection rate of omitted steps in the assembly process reaches 98.5%, and the missed-detection rate is reduced to <1.5%, greatly improving the stability of product quality. At the same time, the false-alarm rate is reduced by -75%, reducing the unnecessary re-inspection workload. In terms of production line change-over, the change-over time is shortened from the original 30 minutes to 5 minutes, significantly improving production efficiency.
FAQ
Can the SkyVision platform adapt to different assembly processes?
Yes. Based on the DaoAI World model, the platform has the ability to generalize across different scenarios. Combined with the zero-code function, on - site personnel can train their own models within hours, adapting to different assembly processes and product types.
How much can the labor cost be reduced by using this platform?
Although the proportion of labor-cost reduction is not directly calculated, the false-alarm rate is reduced by -75% and the change-over time is shortened to 5 minutes. This reduces the labor input in re-inspection and change-over, indirectly reducing the labor cost.
How is the data security of the platform guaranteed?
The edge box of the platform can process and analyze video data locally, realizing 100% local data storage without leaving the site, effectively ensuring data security.