Predicting And Avoiding Failures In Automotive Chips


Semiconductor Engineering sat down to discuss automotive electronics reliability with Jay Rathert, senior director of strategic collaborations at KLA; Dennis Ciplickas, vice president of advanced solutions at PDF Solutions; Uzi Baruch, vice president and general manager of the automotive business unit at OptimalPlus; Gal Carmel, general manager of proteanTecs' Automotive Division; Andre van de ... » read more

Part Average Tests For Auto ICs Not Good Enough


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

Design For Reliability


Circuit aging is emerging as a mandatory design concern across a swath of end markets, particularly in markets where advanced-node chips are expected to last for more than a few years. Some chipmakers view this as a competitive opportunity, but others are unsure we fully understand how those devices will age. Aging is the latest in a long list of issues being pushed further left in the desig... » read more

Modeling PCBs For Common Causes Of Failure


By Theresa Duncan and Michael Blattau When designing printed circuit boards (PCBs), keep in mind the major causes of electronic failure: thermal cycling, vibration, and mechanical shock and drop. You can perform a variety of physical tests to determine how and why electronics fail, however, a much faster and cost-effective solution is PCB modeling and simulation. When simulation is used i... » read more

What Do Feedback Loops For AI/ML Devices Really Show?


AI/ML is being designed into an increasing number of chips and systems these days, but predicting how they will behave once they're in the field is, at best, a good guess. Typically, verification, validation, and testing of systems is done before devices reach the market, with an increasing amount of in-field data analysis for systems where reliability is potentially mission- or safety-criti... » read more

Why Improving Auto Chip Reliability Is So Hard


Tools and ecosystems that focus on reliability and the long-term health of chips are starting to coalesce for the automotive electronics industry. Data gleaned from a chip’s lifecycle — design, verification, test, manufacturing, and in-field operation — will become key to achieving the longevity, reliability, functional safety, and security of newer generations of automobiles. Having s... » read more

A View Across The Siliconscape


What would it look like if you had the magical ability to look inside a chip and cast your eyes across the tumultuous activities within the silicon itself? If you could gaze into the die and see the real-time peaks and troughs of voltage supply, stressed areas with high activity and heat and areas of calm where uneven workloads create idle processor cores. A vision of the chip landscape, seasca... » read more

Achieving Physical Reliability Of Electronics With Digital Design


By John Parry and G.A. (Wendy) Luiten With today’s powerful computational resources, digital design is increasingly used earlier in the design cycle to predict zero-hour nominal performance and to assess reliability. The methodology presented in this article uses a combination of simulation and testing to assess design performance, providing more reliability and increased productivity. ... » read more

Improving Automotive Electronic Hardware With SAE J3168


By Theresa Duncan and Craig Hillman The race is on for fully autonomous vehicles. Industry giants like Tesla, Google, Uber and almost all major automotive companies are competing to deliver state-of-the-art self-driving vehicles. However, the development of new, cutting-edge technologies demands a similar wave of reliability, repairability and warranty standards that automotive manufactur... » read more

Why AI Systems Are So Hard To Predict


AI can do many things, but how to ensure that it does the right things is anything but clear. Much of this stems from the fact that AI/ML/DL systems are built to adapt and self-optimize. With properly adjusted weights, training algorithms can be used to make sure these systems don't stray too far from the starting point. But how to test for that, in the lab, the fab and in the field is far f... » read more

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