Machine-Learning based TCAD Optimization Method for Next Generation BCD Process Development
Jaehyun Yoo, Yongwoo Jeon, Dawon Jung, Junhyuk Kim, Jisu Ryu, Uihui Kwon, Dae Sin Kim, Kwangtae Kim, Yongdon Kim, Lee Kyu-Ok, Jeahyun Jung, OhKyum Kwon
Abstract
An automatic optimization methodology based on AI algorithm is proposed to achieve multi-targeting of various devices in 0.13 μm next BCD process development. The optimized process conditions are simultaneously provided with satisfying various ET-specs of the BCD devices from our method and TCAD analysis. The method has practically been applied to well ion implantation processes shared with seven different devices, and its targeting rate of 87% has been verified through silicon evaluation. Its turnaround time (TAT) is reduced by 90% compared to conventional procedure.
Topics & Concepts
Process (computing)Computer scienceTurnaround timeElectronic engineeringEngineeringOperating systemIntegrated Circuits and Semiconductor Failure AnalysisIndustrial Vision Systems and Defect DetectionVLSI and Analog Circuit Testing