Inspection, Metrology Challenges Grow For SiC


Inspection and metrology are becoming more critical in the silicon carbide (SiC) industry amid a pressing need to find problematic defects in current and future SiC devices. Finding defects always has been a challenging task for SiC devices. But it’s becoming more imperative to find killer defects and reduce them as SiC device vendors begin to expand their production for the next wave of a... » read more

Challenges And Solutions For Silicon Wafer Bevel Defects During 3D NAND Flash Manufacturing


As semiconductor technology scales down in size, process integration complexity and defects are increasing in 3D NAND flash, partially due to larger stack deposits and thickness variability between the wafer center and the wafer edge. Industry participants are working to reduce defect density at the wafer edge to improve overall wafer yield. Attention has focused on common wafer bevel defects s... » read more

New Imaging Tech Finds Buried Defects


By Shinsuke Mizuno and Vadim Kuchik Defects and contamination on the wafer can slow process development times and limit performance and yield. As chips get more complex, more defects can become buried within the increasing number of layers in the design. Finding and analyzing these buried defects is a major challenge for the industry, especially during the early learning cycles of new manufa... » read more

Breakthrough For Scan Diagnosis With Machine Learning


Cell-aware diagnosis is a new and effective way to detect defects inside standard cells. Industry standard failure analysis (FA) results from a major foundry show that cell-aware diagnosis is very effective at increasing the resolution of the diagnosis by reducing the number of suspects in cell-internal defect data. With advanced technology nodes, we have more complex layout structures and f... » read more

Gaps Emerge In Automotive Test


Demands by automakers for zero defects over 18 years are colliding with real-world limitations of testing complex circuitry and interactions, and they are exposing a fundamental disconnect between mechanical and electronic expectations that could be very expensive to fix. This is especially apparent at leading-edge nodes, where much of the logic is being developed for AI systems and image se... » read more

Making AI More Dependable


Ira Leventhal, vice president of Advantest’s new concept product initiative, looks at why AI has taken so long to get going, what role it will play in improving the reliability of all chips, and how to use AI to improve the reliability of AI chips themselves. » read more

E-Beam Review And CD Measurement Revolutionizes Display Yield Management


Fundamental changes are occurring in the display industry, driven by demands for higher-resolution screens and other capabilities for both mobile and TV applications. To meet these demands, the display technology roadmap in this article calls for innovations in materials, processes and device technology. Critical requirements include smaller design rules and the adoption of a range of materi... » read more

The 3 Main Obstacles To Zero DPPM And How To Overcome Them


As we all well know, there are multiple mission critical applications in today’s “Age of Smart” that are calling for zero DPPM (defective parts per million) in semiconductors and electronic systems. In industries such as automotive, medical, aerospace, and more, where lives are at stake, defective parts are not an option. The quality imperative However, with the ever-growing complexi... » read more

Finding Defects In Chips With Machine Learning


Chipmakers are using more and different traditional tool types than ever to find killer defects in advanced chips, but they are also turning to complementary solutions like advanced forms of machine learning to help solve the problem. A subset of artificial intelligence (AI), machine learning has been used in computing and other fields for decades. In fact, early forms of machine learning ha... » read more

Using Sensor Data To Improve Yield And Uptime


Semiconductor equipment vendors are starting to add more sensors into their tools in an effort to improve fab uptime and wafer yield, and to reduce cost of ownership and chip failures. Massive amounts of data gleaned from those tools is expected to provide far more detail than in the past about multiple types and sources of variation, including when and where that variation occurred and how,... » read more

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