Precise Control Needed For Copper Plating And CMP


Chipmakers are relying on machine learning for electroplating and wafer cleaning at leading-edge process nodes, augmenting traditional fault detection/classification and statistical process control in order to extend the usefulness of copper interconnects. Copper is well understood and easy to work with, but it is running out of steam. At 5nm and below, copper plating tools are struggling to... » read more

Predicting And Preventing Process Drift


Increasingly tight tolerances and rigorous demands for quality are forcing chipmakers and equipment manufacturers to ferret out minor process variances, which can create significant anomalies in device behavior and render a device non-functional. In the past, many of these variances were ignored. But for a growing number of applications, that's no longer possible. Even minor fluctuations in ... » read more

Pressure Builds On Failure Analysis Labs


Failure analysis labs are becoming more fab-like, offering higher accuracy in locating failures and accelerating time-to-market of new devices. These labs historically have been used for deconstructing devices that failed during field use, known as return material authorizations (RMAs), but their role is expanding. They now are becoming instrumental in achieving first silicon and ramping yie... » read more

Using AI To Improve Metrology Tooling


Virtual metrology is carefully being added into semiconductor manufacturing, where it is showing positive results, but the chip industry is proceeding cautiously. The first use of this technology has been for augmenting existing fab processes, such as advanced process control (APC). Controlling processes and managing yield generally do not require GPU processing and advanced algorithms, so t... » read more

How AI/ML Improves Fab Operations


Chip shortages are forcing fabs and OSATs to maximize capacity and assess how much benefit AI and machine learning can provide. This is particularly important in light of the growth projections by market analysts. The chip manufacturing industry is expected to double in size over the next five years, and collective improvements in factories, AI databases, and tools will be essential for doub... » read more

High-Volume Manufacturing Device Overlay Process Control


By Honggoo Leea, Sangjun Hana, Jaeson Wooa, DongYoung Leea, ChangRock Songa, Hoyoung Heob, Irina Brinsterb, DongSub Choic, John C. Robinsonb aSK Hynix, 2091, Gyeongchung-daero, Bubal-eub, Icheon-si, Gyeonggi-do, 467-701, Korea bKLA-Tencor Corp., 8834 N. Capital of Texas Hwy, Austin, TX 78759 cKLA-Tencor Korea, Starplaza bldg.., 53 Metapolis-ro, Hwasung City, Gyeonggi-do, Korea Abstract ... » read more

Chip Manufacturing Data Now Requires Cloud Techniques


The parameters in semiconductor manufacturing are growing so large that an analysis method similar to what’s currently used for big data is now required. The good news is that big data analysis techniques, which process a vast amount of data such as search data and communication logs in the cloud, is entirely applicable to the data of semiconductor process. Photo 1: Opening view of AEC... » read more