借用发货通知书-SAP26080501460006-贵州赛卡司测控技术有限公司-文飘

As the computing infrastructure construction cycle enters full swing, liquid cooling solutions have definitively replaced traditional air cooling as the mainstream thermal management configuration for AI data centers, high-end servers, energy storage power stations, and new energy vehicle thermal management systems. The complete liquid cooling industry chain has now entered the phase of domestic mass production and capacity expansion.

Looking across the entire liquid cooling industry architecture, the upstream segment encompasses the processing and manufacturing of core components including cold plates, vapor chambers (VCs), CDU distribution units, coolants, and pipeline sealing fittings. The midstream focuses on liquid cooling system integration and thermal solution design. The downstream connects to end-user applications such as internet data center server rooms, supercomputing centers, new energy vehicle manufacturers, and industrial and commercial energy storage systems. Throughout this entire chain, VCs and micro-channel cold plates serve as the core carriers of heat transfer. Their processing quality directly determines the heat exchange efficiency, sealing performance, and long-term operational stability of liquid cooling systems. Dimension measurement parameters—including flatness, external dimensions, positioning hole positional tolerances, and flow channel depth—have become critical quality control priorities for liquid cooling component manufacturing.

At the current stage, upstream processing plants in the liquid cooling industry chain universally face inspection upgrade challenges. For the flatness inspection of VCs and aluminum alloy cold plates in particular, traditional measurement methods can no longer accommodate the demands of high-volume production and micron-level tolerance control. VCs are predominantly ultra-thin copper-aluminum composite sheets with thicknesses generally ranging from 0.3 mm to 2 mm. After brazing, they are highly susceptible to thermal warping and localized concave deformation. Micro-channel cold plates are prone to stress-induced deformation in welded areas, with flatness tolerance requirements for chip contact zones reaching as stringent as 3 μm to 8 μm. When flatness exceeds tolerance, microscopic gaps form between the vapor chamber and the GPU or CPU heat source, substantially increasing contact thermal resistance. During computing operations, this leads to localized hot spots and chip throttling, and in severe cases, causes uneven compression of sealing gaskets and coolant leakage—posing safety hazards for downstream data center operations.

Traditional flatness inspection methods fall into three categories, each with distinct shortcomings. The first involves manual dial gauge testing with a granite surface plate, which only samples dozens of discrete points to calculate flatness values. This method cannot reconstruct the complete curved surface morphology of an entire vapor chamber, leaving localized depressions and warping defects easily overlooked. Manual sampling errors are significant, and inspection of a single workpiece takes 2 to 5 minutes—far too inefficient for high-volume production line sampling. The second method uses CMM contact measurement. While measurement accuracy is adequate, the contact probe pressing against thin-wall vapor chambers easily causes deformation and surface scratches. Additionally, CMM scanning of a single piece exceeds 15 minutes, making it suitable only for laboratory first-article inspection and incapable of integration into production lines for 100% inspection. The third method—conventional 2D vision measuring machines—possesses only planar contour dimension measurement capability and lacks Z-axis height acquisition modules. These machines can measure length, width, aperture, and other 2D dimensions but cannot collect height point cloud data, rendering them unable to perform full-surface flatness calculation and creating inspection blind spots. As liquid cooling industry capacity continues to scale up, upstream manufacturers urgently need an integrated inspection solution that combines dimension measurement, full-surface flatness scanning, non-contact detection, and automated production-line adaptability. Sinowon's line scan laser image measuring instrument was developed precisely to meet this need.

With over a decade of deep expertise in the field of optical dimension measurement, Sinowon has developed the AI-powered line scan laser image measuring instrument featuring a multi-sensor architecture that integrates 2D vision with line scan laser technology. This instrument covers the entire inspection workflow—from incoming material inspection and in-process to final outgoing goods inspection. It can perform conventional dimension measurements including length, width, positioning hole position accuracy, and flow channel opening dimensions, while also leveraging a high-speed line scan laser module to capture full-surface Z-axis height point clouds. AI algorithms then fit a reference plane and calculate the full-surface flatness PV value of the entire board—closing the capability gap of traditional vision measuring machines that cannot measure flatness. The equipment features a natural granite monolithic base that isolates measurement accuracy deviations caused by environmental vibration. The three-axis closed-loop servo drive system, equipped with a glass scale grating ruler achieving 0.1 μm resolution, delivers flatness repeat measurement accuracy stably controlled within ±0.8 μm—fully matching the stringent tolerance standards of high-end liquid cooling vapor chambers.

Addressing the material-specific challenges of highly reflective copper vapor chambers and diffuse-reflective aluminum cold plates that make imaging difficult, Sinowon's line scan laser image measuring instrument is equipped with an 8-zone annular programmable cold light source paired with an HDR high-dynamic imaging system. The system automatically switches light source modes based on the workpiece material, eliminating edge recognition deviations caused by metallic reflections. The built-in self-developed AI deep-learning edge detection algorithm can autonomously distinguish between the actual board edge and processing burrs, capturing contour boundaries at sub-pixel accuracy to ensure precise dimension measurement data for length, width, and hole dimensions. In terms of flatness inspection logic, the line scan laser scans the entire vapor chamber surface at a speed of 48,000 profile lines per second, generating millions of 3D point cloud data points. The system automatically employs the least squares method to fit a standard reference plane, calculates the height deviation of each point relative to the reference plane, and automatically classifies three types of defects—overall warping, localized concavity, and welding deformation—while ing the coordinates of deformed locations. Process engineers can use the flatness deformation distribution data to reversely optimize brazing and stamping processes, reducing vapor chamber defect rates at the source.

Deployed in liquid cooling industry production scenarios, the equipment achieves a multi-purpose inspection model: during incoming material inspection, it screens vapor chamber external dimensions and thickness; after stamping and brazing processes, it performs inspection of board flatness changes to monitor processing deformation; at the finished goods stage, it completes all 2D dimension measurements plus full-surface flatness inspection in a single, highly integrated workflow. Compared to the traditional model of using calipers, CMM, and 2D vision measuring machines separately, a single line scan laser image measuring instrument can replace three conventional inspection devices, reducing manual labor input by 65% and shortening the complete inspection cycle for a single vapor chamber to 18 seconds. The instrument can be placed offline in quality labs for precision finished goods inspection, or integrated with transfer modules into automated production lines for 100% online inspection of vapor chambers.

As the domestic production of the liquid cooling industry chain continues to accelerate, the quality control capabilities of upstream component processing plants will determine the market competitiveness of domestic liquid cooling solutions. Sinowon's line scan laser image measuring instrument fills the technical gap in integrated vapor chamber flatness and dimension measurement, addressing the industry pain points of easily scratched thin-wall soft liquid cooling plates, challenging full-surface flatness inspection, and low mass-production inspection efficiency through a non-contact multi-sensor measurement approach. Looking ahead, as cold plate liquid cooling continues to dominate the data center thermal management market, the demand for precision vapor chamber inspection will continue to grow. Sinowon will further iterate its AI vision algorithms and laser scanning modules to meet customized measurement requirements across different segments of the liquid cooling industry chain, supporting intelligent quality upgrades in liquid cooling upstream manufacturing.