- Lost yield from stokasty costs chipmakers billions by advanced process nodes
- Current process management methods are not enough to solve stochastic errors with high volume
- New WhitePaper outlines design and measuring solutions to close stochastic cleft
A new whitepaper has claimed that the semiconductor industry is losing billions of dollars due to something few off the field has heard of: Stochastic variation.
This kind of random pattern variation is now considered the biggest obstacle to achieving high yields at the most advanced process nodes.
The paper was contributed by Austin, Texas-based Fractilia, whose CTO, Chris Mack, noticed, “Stochastic variation contributes to delays on multi-billion dollars to introduce advanced process technology in the production of high volume.”
Affects yield, performance and reliability
Mack further explained that the current process management strategies have not been able to tackle these random effects.
“Closing Stochastics Gap requires completely different methodologies that unit manufacturers need to validate and adopt,” Mack said.
Fractilia defines this “stokastic gap” as the difference between what can muster in research and what can be reliably produced by acceptable yields.
In the heart of this hole is a coincidence that is rooted in the physics of materials, molecules and light sources used in chip production.
Although these effects were once insignificant, they now consume a growing proportion of production error budget.
“We have seen our customers make close features as small as 12 nanometers in research and development,” said Mack. “But when they try to move it to manufacture, stochastic failures affect their ability to achieve acceptable benefits, performance and reliability.”
The problem has grown along with the increase in EUV and high-na EUV lithography. These progress has enabled chipmakers to try even less features, but also made them more vulnerable to stochastic defects.
Unlike conventional variation, this type cannot be removed with tighter controls, it must be controlled with probability-based design and measurement techniques.
“Stochastics Gap is an industry -inclusive problem,” Mack said. “This problem can be minimized and controlled, but it all starts with accurate stochastic measurement technology.”
Whitepaper, which you can download here, includes an analysis of the problem and suggests stochastic-attention design, material innovation and updated process management as the path forward.
