Big Challenges In Verifying Cyber-Physical Systems


Semiconductor Engineering sat down to discuss cyber-physical systems and how to verify them with Jean-Marie Brunet, senior director for the Emulation Division at Siemens EDA; Frank Schirrmeister, senior group director for solution marketing at Cadence; Maurizio Griva, R&D Manager at Reply; and Laurent Maillet-Contoz, system and architect specialist at STMicroelectronics. This discussion was... » 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

Automotive Test Moves In-System


With the electrification of automobiles, it’s not enough to test the new electronics thoroughly at the end of the manufacturing process. Safety standards now require that tests be performed live, in the field, with contingency plans should a test fail. “We see clear demand from the automotive semiconductor supply chain for design functionality specifically aimed at in-system monitoring,�... » read more

Data Issues Mount In Chip Manufacturing


For yield management systems the old calculation adage, "garbage in/garbage out" still rings true. Aligning and cleaning data remains a dirty business. With the increased value in data in the semiconductor supply chain, there now are essentially two supply chains running in parallel. One involves the physical product being created, while the other includes the data associated with each proce... » read more

Parallel RF Test For Next-Generation Communications


The test economics of state-of-the-art smartphones, tablets and routers demand highly parallel RF test. We are addressing this next wave in RF communications test, enabled by Wi-Fi 6E, operating in the 6GHz band and coming up to 7.125GHz. This forthcoming update to the Wi-Fi standard will extend the features and capabilities, including higher performance, lower latency, and faster data rates fo... » read more

Testing VCSEL Devices On-Wafer


Vertical-Cavity Surface-Emitting Lasers, or VCSELs, are seeing unparalleled demand, thanks to new uses for them in smartphone and automotive applications. 3D sensing for facial recognition is the key application in smartphones, with up to three VCSEL dies being integrated into a single phone. Emerging automotive applications such as driver monitoring, infotainment control and LiDAR will provide... » read more

Metrology at Automated Test Equipment Manufacturers


New technologies require an efficient qualification infrastructure to determine and qualify technical specifications. Metrology is the science which determines the acknowledged specification setting process based on proven international standards. This paper describes metrology and its role and benefits in automated test equipment business. By Piotr Skwierawski and Ralf Haefner. Click her... » read more

Better Quality RTL


How do you measure the quality of RTL? Philippe Luc, director of verification at Codasip, talks about identifying bugs, improving the overall quality of the verification, what happens when different blocks are used in a design, and how to improve efficiency in the verification process. » 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

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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