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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.
Proceedings Title
2017 IEEE Big Data
Conference Dates
December 11-14, 2017
Conference Location
Boston, MA, US


virtual data, synthetic data, data generation, smart manufacturing


Libes, D. , Lechevalier, D. and Jain, S. (2017), Issues in Synthetic Data Generation for Advanced Manufacturing, 2017 IEEE Big Data, Boston, MA, US, [online], (Accessed June 13, 2024)


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Created December 10, 2017, Updated October 12, 2021