Abstract
Optimizing sustainable manufacturing processes using cyber-physical systems （CPS） to improve product lifecycle efficiency,
reduce costs, and respond flexibly to changing markets and needs is attracting increasing attention. This paper provides an overview
of CPS and then presents examples of AI applications in the field of advanced metrology, which is particularly important for
obtaining good virtual models. The potential of data-driven modeling that leverages human knowledge and experience will be
demonstrated. In addition, we describe a method for extracting human-interpretable equations from data to support feedback for
system improvement. Since these methods are not yet in practical use and CPS is still in the development stage, it is expected that
collaboration among various engineers will increase.
