In the production of automotive parts, the quality inspection of the fastener tightening process is crucial. WeLinkirt provides an efficient and accurate inspection solution for the automotive industry with advanced AI vision technology.
User Scenario: On the fastener tightening production line of a leading automotive parts manufacturer, it is necessary to detect the tightening status of fasteners on various automotive parts. The products cover a variety of key components such as engine blocks and transmission casings. The main detection objects are fasteners such as bolts and nuts after tightening to ensure that their tightening degree meets the production standards.
Pain Points: The traditional detection method mainly relies on manual labor, which is not only inefficient but also has a high missed detection rate of up to 5% and a false alarm rate of about 3%. Manual detection also has the problems of high labor cost and high labor intensity. Moreover, when changing production models, it takes about 1 hour to debug the detection equipment, which seriously affects the production efficiency. In addition, manual detection is difficult to meet the requirements of real-time full inspection on high-speed production lines and cannot guarantee the stability and consistency of product quality.
Technical Principle
WeLinkirt uses advanced AI algorithms and high-precision imaging technology to solve the above problems. In terms of AI algorithms, through a deep convolutional neural network, a large number of fastener tightening images are trained and learned, enabling the system to accurately identify the tightening status of fasteners of different types and specifications. The deep convolutional neural network has a powerful feature extraction ability and can extract subtle features such as the angle of the bolt head and the position of the nut from the image to determine whether the tightening is qualified.
- In terms of imaging technology, a self-developed 3D camera is used for image acquisition. The 3D camera can obtain the three-dimensional morphology information of fasteners. Compared with traditional 2D imaging, it can more comprehensively and accurately reflect the actual state of fasteners. Through the three-dimensional morphology reconstruction technology, the collected three-dimensional data is processed to generate a clear and accurate three-dimensional model, providing more abundant information for subsequent detection and analysis.
- The reason why this technical principle combining AI algorithms and 3D imaging is effective is that it fully utilizes the intelligent analysis ability of AI and the high-precision information of 3D imaging, and can accurately identify the tightening state of fasteners in a complex production environment, greatly improving the accuracy and reliability of detection.
WeLinkirt Solution and Product Introduction
WeLinkirt provides the DaoAI AI AOI software system and the DaoAI 2D / 3D AI AOI equipment. The DaoAI AI AOI software system has powerful feature recognition capabilities. Using the visual basic model, it can complete 0-code automatic programming in 5 minutes with only one good product. Through the APDT positive sample/few-sample learning function, the model training can be completed with only 1-20 good product images, greatly shortening the model training time. At the same time, the semantic false alarm filtering function can effectively reduce false alarms and improve the accuracy of detection.
WeLinkirt's technology brings an efficient and accurate solution to the fastener tightening detection of automotive parts.
The DaoAI 2D / 3D AI AOI equipment is equipped with a self-developed 3D camera and can perform three-dimensional morphology reconstruction, which can detect hidden welds, coplanarity, and micron-level morphology. In the fastener tightening detection, this equipment can clearly obtain the three-dimensional information of fasteners and accurately judge the tightening state. The equipment supports SDK / API / Docker deployment and can achieve 100% local private deployment to ensure that data does not leave the factory and guarantee data security.
Quantitative Results: After adopting WeLinkirt's solution, the detection rate of fastener tightening detection has increased to over 98%, the missed detection rate has been reduced to <2%, and the false alarm rate has been reduced by -70%. The model change time has been shortened from about 1 hour to 5 minutes, greatly improving production efficiency and meeting the requirements of real-time full inspection on high-speed production lines.