In-Sight 3900 Series
In-Sight 3900 is a high-speed AI machine vision system built for high-throughput production lines, with powerful computing and embedded AI for processing high-resolution images and advanced inspections.
Sales:
The microscopic edge defects and burr edge problems that are the result of wafer dicing can ruin downstream packaging and testing. Traditional inspection can't tell the difference between normal cut marks and actual quality issues in fast-paced cleanroom environments. Fortunately, Cognex AI-powered vision systems make wafer dicing inspection reliable and fast enough for semiconductor fab demands.
When running wafer dicing operations in semiconductor fabs, edge quality inspection is critical to ensuring dies survive downstream packaging and testing. The dicing process must deliver clean cuts without excessive chipping, edge burrs, or microcracks that compromise device integrity. Each die that passes inspection carries a significant investment in layering lithography and etching steps, making accurate defect detection essential for yield protection and long-term reliability.
Defects such as chipping, debris, and sidewall cracks directly affect chip performance and longevity. In wafer-level chip scale packages (WLCSP), thin dies are particularly vulnerable to handling stress, while standard dies require pristine edges for steps like wire bonding. In both cases, edge defects pose serious reliability risks. High throughput requirements, combined with strict cleanroom integration standards, make traditional manual inspection inadequate and driving the need for automated, high-speed inspection solutions purpose-built for semiconductor manufacturing.
Wafer dicing inspection becomes especially difficult at microscopic scales, where the challenge lies in separating true defects from normal cut marks. The wafer sawing process naturally produces variable chipping and edge burrs that look different on every die, while WLCSP sidewall inspection introduces complex structural layers that can obscure microcracks. Traditional rule-based vision systems struggle in these environments, as they can't reliably distinguish acceptable dicing variations from quality-critical defects.
Key challenges that limit conventional wafer dicing inspection include:
Ultimately, rule-based inspection cannot scale to the complexity of wafer dicing. With constantly changing cut characteristics and countless acceptable variations, trying to program every possible edge condition becomes an impractical—and costly—approach.
Cognex AI-powered technology transforms the difficult, error-prone task of wafer dicing inspection with reliable, automated quality control built for semiconductor fabs. By training on representative images of both acceptable and defective die edges, our AI tools learn to distinguish true quality-critical defects from normal dicing marks while maintaining the fast inspection speeds semiconductor fabs require.
How Cognex AI improves wafer dicing inspection:
The result is consistent edge quality and maximum yield—only defective dies are rejected, while valuable devices that rule-based systems might misclassify are preserved. For WLCSP applications, this means dependable microcrack detection that prevents field failures without driving up false rejects.
Whether monitoring sawing quality, tracking blade wear, or verifying die edges before assembly, Cognex delivers the inspection accuracy fabs need—without slowing down production. And to keep production running at top speed, Cognex backs our products with a global network of support experts and a vast library of training and help content that’s available when and how you want it.