Any object that can be modeled in 3D can also be used for synthetic data generation. Below are just a few possible use cases of synthetic data generation:
Generating different angles of a piece of machinery in order to identify the different components and parts.
Generating images of biological cells to train a computer vision model (e.g., identifying different cell types or distinguishing between cancerous and non-cancerous cells).
Generating various manufacturing defects (e.g., cracks, missing parts, misshaped items, etc.) so that a computer vision model can learn to identify defective products.