Issues in Synthetic Data Generation for Advanced Manufacturing
Donald E. Libes, David Lechevalier, Sanjay Jain
Research into advanced manufacturing requires data for analysis. There is limited access to real-world data and a need for more data of varied types and larger quantity. This paper explores the issues, and identifies challenges, and suggests requirements and desirable features in the generation of virtual data. These issues, requirements, and features can be used for researchers to build virtual data generators and gain experience that will provide data to data scientists while at the same time, avoiding known or potential problems. This, in turn, will lead to better requirements and features in future virtual data generators.
, Lechevalier, D.
and Jain, S.
Issues in Synthetic Data Generation for Advanced Manufacturing, 2017 IEEE Big Data, Boston, MA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=921398
(Accessed December 2, 2023)