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

Test Connections Clean Up With Real-Time Maintenance


Test facilities are beginning to implement real-time maintenance, rather than scheduled maintenance, to reduce manufacturing costs and boost product yield. Adaptive cleaning of probe needles and test sockets can extend equipment lifetimes and reduce yield excursions. The same is true for load board repair, which is moving toward predictive maintenance. But this change is much more complicate... » read more

Big Payback For Combining Different Types Of Fab Data


Collecting and combining diverse data types from different manufacturing processes can play a significant role in improving semiconductor yield, quality, and reliability, but making that happen requires integrating deep domain expertise from various different process steps and sifting through huge volumes of data scattered across a global supply chain. The semiconductor manufacturing IC data... » read more