Anne Meixner

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Anne Meixner is a contributing editor at Semiconductor Engineering. She has 30+ years in the semiconductor industry. She became fascinated by defects in the semiconductor manufacturing process as a young engineer at IBM. Over that period, she has focused on test methodology with emphasis on mixed-signal and analog DFT and test. As a technical communicator she takes complex ideas and explains them in consumable understandable pieces. Meixner has worked at IBM, Carnegie Mellon University and Intel. She holds three U.S. patents and her peers have recognized her work with two best papers at IEEE International Test Conference. She founded The Engineers’ Daughter in 2015 to consult on semiconductor testing and to coach engineers.

Author's Latest Posts

Hunting For Hardware-Related Errors In Data Centers
By Anne Meixner - 07 Feb, 2023 - Comments: 2

The semiconductor industry is urgently pursuing design, monitoring, and testing strategies to help identify and eliminate hardware defects that can cause catastrophic errors. Corrupt execution errors, also known as silent data errors, cannot be fully isolated at test — even with system-level testing — because they occur only under specific conditions. To sort out the environmental condit... » read more

Ramping Up IC Predictive Maintenance
By Anne Meixner - 07 Feb, 2023 - Comments: 0

The chip industry is starting to add technology that can predict impending failures early enough to stave off serious problems, both in manufacturing and in the field. Engineers increasingly are employing in-circuit monitors embedded in SoC designs to catch device failures earlier in the production flow. But for ICs in the field, data tracing from design to application use only recently has ... » read more

Screening For Silent Data Errors
By Anne Meixner - 10 Jan, 2023 - Comments: 0

Engineers are beginning to understand the causes of silent data errors (SDEs) and the data center failures they cause, both of which can be reduced by increasing test coverage and boosting inspection on critical layers. Silent data errors are so named because if engineers don’t look for them, then they don’t know they exist. Unlike other kinds of faulty behaviors, these errors also can c... » read more

Adopting Predictive Maintenance On Fab Tools
By Anne Meixner - 06 Dec, 2022 - Comments: 0

Predictive maintenance, based on more and better sensor data from semiconductor manufacturing equipment, can reduce downtime in the fab and ultimately cut costs compared with regularly scheduled maintenance. But implementing this approach is non-trivial, and it can be disruptive to well-honed processes and flows. Not performing maintenance quickly enough can result in damage to wafers or the... » read more

Test Connections Clean Up With Real-Time Maintenance
By Anne Meixner - 08 Nov, 2022 - Comments: 0

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

Why Silent Data Errors Are So Hard To Find
By Anne Meixner - 11 Oct, 2022 - Comments: 1

Cloud service providers have traced the source of silent data errors to defects in CPUs — as many as 1,000 parts per million — which produce faulty results only occasionally and under certain micro-architectural conditions. That makes them extremely hard to find. Silent data errors (SDEs) are random defects produced in manufacturing, not a design bug or software error. Those defects gene... » read more

The Drive Toward More Predictive Maintenance
By Anne Meixner - 08 Sep, 2022 - Comments: 0

Maintenance is a critical behind-the-scenes activity that keeps manufacturing facilities running and data centers humming. But when not performed in a timely manner, it can result in damaged products or equipment, or significant system/equipment downtime. By shifting from scheduled maintenance to predictive maintenance, factories and electronic system owners can reap substantial benefits, in... » read more

Making The Most Of Data Lakes
By Anne Meixner - 09 Aug, 2022 - Comments: 0

Having all the semiconductor data available is increasingly necessary for improving manufacturability, yield, and ultimately the reliability of end devices. But without sufficient knowledge of relationships between data from different processes and computationally efficient data structures, the value of any data is significantly reduced. In the semiconductor industry, reducing waste, decreas... » read more

Finding Frameworks For End-To-End Analytics
By Anne Meixner - 12 Jul, 2022 - Comments: 0

End-to-end analytics can improve yield and ROI on tool purchases, but reaping those benefits will require common data formats, die traceability, an appropriate level of data granularity — and a determination of who owns what data. New standards, guidelines, and consortium efforts are being developed to remove these barriers to data sharing for analytics purposes. But the amount of work req... » read more

Removing Barriers For End-To-End Analytics
By Anne Meixner - 07 Jun, 2022 - Comments: 0

Parties are coming together, generating guidelines for sharing data from IC design and manufacturing through end of life, setting the stage for true end-to-end analytics. While the promise of big data analytics is well understood, data sharing through the semiconductor supply chain has been stymied by an inability to link together data sources throughout the lifecycle of a chip, package, or ... » read more

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