  Patent data have long been used for engineering design research because of
its large and expanding size, and widely varying massive amount of design
information contained in patents. Recent advances in artificial intelligence
and data science present unprecedented opportunities to develop data-driven
design methods and tools, as well as advance design science, using the patent
database. Herein, we survey and categorize the patent-for-design literature
based on its contributions to design theories, methods, tools, and strategies,
as well as the types of patent data and data-driven methods used in respective
studies. Our review highlights promising future research directions in patent
data-driven design research and practice.
