  The etching process is one of the most important processes in semiconductor
manufacturing. We have introduced the state-of-the-art deep learning model to
predict the etching profiles. However, the significant problems violating
physics have been found through various techniques such as explainable
artificial intelligence and representation of prediction uncertainty. To
address this problem, this paper presents a novel approach to apply the
inductive biases for etching process. We demonstrate that our approach fits the
measurement faster than physical simulator while following the physical
behavior. Our approach would bring a new opportunity for better etching process
with higher accuracy and lower cost.
