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In order to promote the deep integration of artificial intelligence technology and advanced manufacturing, and build a bridge between university scientific research achievements and enterprise production needs, on April 29, organized by the Administrative committee of Nanjing Lishui High-tech Industry Development Zone and Nanjing Lishui High-tech Industry Investment Co., LTD., The “Liyang Warehouse” Industrial intelligent Testing School Enterprise Production, education and Research Technology Application Salon jointly organized by Xiaohu Science and Technology and Nanjing University of Science and Technology Park was successfully held in the road show Center of the Xingzhuang Science and Technology Industrial Park project. The event focused on core directions such as AI industrial defect detection, production line automation upgrading, and collaborative transformation of production, teaching and research, bringing together enterprise technical leaders, industry experts and university teams to have in-depth exchanges, and jointly promoting digital technology to enable the high-quality development of Lishui manufacturing industry.
At the beginning of the activity, the Lishui High-tech Zone promoted the business environment of Lishui High-tech Zone, comprehensively demonstrating the advantages of Lishui High-tech Zone as a fertile land for industrial innovation from the aspects of industrial carrier, policy support, talent guidance and education, scientific and technological innovation services, and supporting security.
Theme Sharing Session
Associate Professor Lu Jianyong from Nanjing University of Science and Technology brought a special report on AI industrial defect detection Technology and practice. Professor Lv systematically explained the core principles, technical architecture and landing advantages of AI defect detection, focusing on the dismantling of two benchmark application scenarios of chip defect detection and road defect detection, and combining real cases such as wafer defect recognition, package 3D measurement, high-precision turbine detection, and automatic recognition of road diseases. In-depth analysis of industrial detection of small and medium-sized target defects, high reflective interference, few-shot learning, complex environment adaptation and other technical difficulties and solutions. He pointed out that AI defect detection can achieve 7×24 hours of uninterrupted operation, significantly reduce labor costs, improve detection accuracy and consistency, and provide a reliable technical path for enterprises to improve quality, reduce costs and increase efficiency.
Interactive communication link
Manager Wu and Professor Lv, technical director of Chang De Cheng Electronics, focused on the automatic detection of PCBA production line, unified control of multiple devices, and central server deployment, focusing on key issues such as multi-production line coordination, unified standard issuance, sub-product instruction adaptation, and test data interconnection.
Longwo Technology and Professor Lu focused on the difficulties of bridge fault detection early warning and structural health monitoring. Aiming at the core issues of long-term monitoring of bridge status, stable deployment of sensors, labeling accuracy of defect samples, and detection reliability of few/difficult samples, they discussed the landing path of the fusion of AI vision and sensing technology, and strengthened the accuracy of early warning and detection stability.
After the salon, the scientific research team of Nanjing University of Science and Technology walked into the production line of Changdecheng Electronics to check the operation status of PCBA production line, product testing process and existing equipment working conditions. The team communicated with the technical staff of the enterprise face to face to understand the actual pain points such as the high rate of manual re-judgment, inconsistent detection standards, missed detection of appearance defects, and rapid switching of multiple models of products in detail. The technical upgrading requirements such as 3D visual inspection, AI algorithm optimization, automatic sorting, and whole process data interconnection were met on the spot. It lays a solid foundation for the subsequent development of customized solutions and the landing of pilot projects.
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