Neuroevolution-Based Network Architecture Evolution in Semiconductor Manufacturing.

ABSTRACT: Promoted model architectures or algorithms are crucial for intelligent manufacturing since developing them takes a lot of trial and error to embed the domain knowledge into the models correctly. Especially in semiconductor manufacturing, the whole processes depend on complicated physical equations and sophisticated fine-tuning. Therefore, we use a neuroevolution-based model to search the optimized architecture automatically. The collector current value at a particular bias of the silicon-germanium (SiGe) heterojunction bipolar transistor, generated by technology computer-aided design (TCAD), is used as the target dataset with six process parameters as the inputs. The processes include oxidation, dry and wet etching, implantation, annealing, diffusion, and chemical-mechanical polishing. Our

SUBMITTER: Feng YW 

PROVIDER: S-EPMC10413832 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature