Improving Yield, Reliability With Data


Big data techniques for sorting through massive amounts of data to identify aberrations are beginning to find a home in semiconductor manufacturing, fueled by new requirements in safety-critical markets such as automotive as well as the rising price of packaged chips in smartphones. Outlier detection—the process of finding data points outside the normal distribution—isn't a new idea. It ... » read more

ON Semiconductor Meets AEC Challenges With Electrothermal Analysis


By Justin Yerger, ON Semiconductor, and Ahmed Eisawy, Mentor, a Siemens Business ON Semiconductor is a leading provider of products for automotive applications that follow the Automotive Electronics Council (AEC Q-100-012) requirements for reliability characterization of smart power devices. In particular, Automotive Smart FET driver ICs present verification challenges when verifying short c... » read more

ON Semiconductor Meets AEC Requirements For Automotive Smart FET Drivers With Eldo Platform’s Electrothermal Analysis


ON Semiconductor is a leading provider of products for automotive applications that follow the Automotive Electronics Council (AEC Q-100-012) requirements for reliability characterization of smart power devices. This case study documents the verification challenges and solutions to validate short circuit reliability of Automotive Smart FET driver ICs according to these AEC requirements. Designe... » read more

Chip Manufacturing Data Now Requires Cloud Techniques


The parameters in semiconductor manufacturing are growing so large that an analysis method similar to what’s currently used for big data is now required. The good news is that big data analysis techniques, which process a vast amount of data such as search data and communication logs in the cloud, is entirely applicable to the data of semiconductor process. Photo 1: Opening view of AEC... » read more