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Improving Yield With Machine Learning


Machine learning is becoming increasingly valuable in semiconductor manufacturing, where it is being used to improve yield and throughput. This is especially important in process control, where data sets are noisy. Neural networks can identify patterns that exceed human capability, or perform classification faster. Consequently, they are being deployed across a variety of manufacturing proce... » read more

E-beam’s Role Grows For Detecting IC Defects


The perpetual march toward smaller features, coupled with growing demand for better reliability over longer chip lifetimes, has elevated inspection from a relatively obscure but necessary technology into one of the most critical tools in fab and packaging houses. For years, inspection had been framed as a battle between e-beam and optical microscopy. Increasingly, though, other types of insp... » read more

Strategies For Faster Yield Ramps On 5nm Chips


Leading chipmakers TSMC and Samsung are producing 5nm devices in high volume production and TSMC is forging ahead with plans for first 3nm silicon by year end. But to meet such aggressive targets, engineers must identify defects and ramp yield faster than before. Getting a handle on EUV stochastic defects — non-repeating patterning defects such as microbridges, broken lines, or missing con... » read more