tag: PAT

What Data Center Chipmakers Can Learn From Automotive
By Anne Meixner - 11 Apr, 2023 - Comments: 2

Automotive OEMs are demanding their semiconductor suppliers achieve a nearly unmeasurable target of 10 defective parts per billion (DPPB). Whether this is realistic remains to be seen, but systems companies are looking to emulate that level of quality for their data center SoCs. Building to that quality level is more expensive up front, although ultimately it can save costs versus having to ... » read more

Coping With Parallel Test Site-to-Site Variation
By Anne Meixner - 09 Nov, 2021 - Comments: 1

Testing multiple devices in parallel using the same ATE results in reduced test time and lower costs, but it requires engineering finesse to make it so. Minimizing test measurement variation for each device under test (DUT) is a multi-physics problem, and it's one that is becoming more essential to resolve at each new process node and in multi-chip packages. It requires synchronization of el... » read more

One Test Is Not Always Enough
By Anne Meixner - 12 Oct, 2021 - Comments: 0

To improve yield, quality, and cost, two separate test parameters can be combined to determine if a part passes or fails. The results gleaned from that approach are more accurate, allowing test and quality engineers to fail parts sooner, detect more test escapes, and ultimately to improve yield and reduce manufacturing costs. New data analytic platforms, combined with better utilization of s... » read more

Geo-Spatial Outlier Detection
By Anne Meixner - 19 Jul, 2021 - Comments: 0

Comparing die test results with other die on a wafer helps identify outliers, but combining that data with the exact location of an outlier offers a much deeper understanding of what can go wrong and why. The main idea in outlier detection is to find something in or on a die that is different from all the other dies on a wafer. Doing this in the context of a die’s neighbor has become easie... » read more

The Emergence Of Inline Screening For High Volume Manufacturing
By KLA - 08 Jun, 2021 - Comments: 0

The semiconductor content of automobiles is growing rapidly in applications where quality is of paramount importance, and automotive manufacturers have taken the lead in driving a “Zero Defect” mentality into their supply chain. The motivation behind this paper started with engagements with semiconductor suppliers as well as automotive manufacturers, where KLA witnessed many clear examples ... » read more

Hunting For Open Defects In Advanced Packages
By Anne Meixner - 17 Mar, 2021 - Comments: 5

Catching all defects in chip packaging is becoming more difficult, requiring a mix of electrical tests, metrology screening, and various types of inspection. And the more critical the application for these chips, the greater the effort and the cost. Latent open defects continue to be the bane of test, quality, and reliability engineering. Open defects in packages occur at the chip-to-substra... » read more

Part Average Tests For Auto ICs Not Good Enough
By Anne Meixner - 24 Feb, 2021 - Comments: 0

Part Average Testing (PAT) has long been used in automotive. For some semiconductor technologies it remains viable, while for others it is no longer good enough. Automakers are bracing for chips developed at advanced process nodes with much trepidation. Tight control of their supply chains and a reliance upon mature electronic processes so far have enabled them to increase electronic compone... » read more

Part Average Test (PAT)
By yieldHUB - 12 Jan, 2021 - Comments: 0

With semiconductor manufacturers producing huge amounts of data, it can be hard to guarantee quality and reliability, even with internal tools. Many companies outsource Part Average Testing (PAT) to a bespoke yield management provider. Provided they meet the standards set out by AEC, the tool will be invaluable in guaranteeing quality and reliability for your customers. Click here to con... » read more

Using Fab Sensors To Reduce Auto Defects
By Anne Meixner - 09 Jun, 2020 - Comments: 0

The semiconductor manufacturing ecosystem has begun collaborating on ways to effectively use wafer data to meet the stringent quality and reliability requirements for automotive ICs. Silicon manufacturing companies are now leveraging equipment and inspection monitors to proactively identify impactful defects prior to electrical test. Using machine learning techniques, they combine the monitor ... » read more

Finding Faulty Auto Chips
By Mark LaPedus - 05 Mar, 2018 - Comments: 1

The next wave of automotive chips for assisted and autonomous driving is fueling the development of new approaches in a critical field called outlier detection. KLA-Tencor, Optimal+, as well as Mentor, a Siemens Business, and others are entering or expanding their efforts in the outlier detection market or related fields. Used in various industries for several years, outlier detection is one... » read more

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2024 SMG   |  Terms of Service  |  Privacy Policy