With Industry 4With the advent of the 0 era, intelligent manufacturing has become the core force to promote industrial development. In this process, computer vision inspection technology plays an increasingly important role in industrial intelligence with its unique advantages and a wide range of application scenarios. From automobile manufacturing to coal mining, from micro parts to macro equipment, computer vision inspection is providing accurate and efficient solutions for industrial production.
In the field of automobile manufacturing, the application of computer vision inspection technology is particularly prominent. Traditional automotive quality inspection relies on manual visual inspection, which is not only inefficient, but also susceptible to human factors, resulting in unstable quality. The introduction of computer vision inspection technology has completely changed this situation. By simulating the human vision system, computer vision inspection technology can quickly and accurately identify the problems of various parts of the car, which greatly improves the efficiency and accuracy of quality inspection.
Taking Geely Lotus as an example, Lenovo deployed an AI visual automatic detection intelligent application solution for it, which realizes a comprehensive quality inspection of multiple units such as the car's power system, exterior accessories, and interior architecture. By adopting the "non-stop detection" technology, the scheme can complete the data collection and analysis of the whole vehicle without the vehicle stopping, which greatly improves the detection efficiency. At the same time, the solution also combines traditional vision applications and AI deep learning to realize the upgrade from semi-artificial anomaly detection to unmanned and fully automatic detection, providing strong support for the intelligent upgrade of the automobile manufacturing industry.
In the field of coal mining, computer vision inspection technology also shows great potential. As an important equipment in coal mine production, the operation of the scraper conveyor directly affects the production efficiency and safety. Traditional inspection methods require manual periodic inspections, which are not only inefficient, but also difficult to detect potential problems. The application of computer vision detection technology can realize real-time monitoring and early warning of scraper conveyor.
The solution developed by Lenovo Shanghai Research Institute captures the scraper operation through a 3D depth camera** and uploads it to the cloud in real time for analysis. The solution can not only collect image data in a dark environment, but also automatically identify signs of wear and damage on the scraper chain conveyor, and issue early warnings in time, providing a strong guarantee for the safety and efficiency of coal mine production.
The wide application of computer vision inspection technology not only reflects the rapid development of industrial intelligence, but also reveals the infinite possibilities of future manufacturing. However, advances in technology have also brought new challenges. How can you further improve the speed of detection while maintaining accuracy? How to better adapt to the testing needs of different environments and different products? These are all questions that we need to think about and solve. But in any case, the emergence of Lenovo's computer vision inspection technology has undoubtedly opened a new door for us and let us see a better future for the manufacturing industry.
Lenovo full-stack intelligence