Enhancing manufacturing operations with synthetic data: a systematic framework for data generation, accuracy, and utility
Vishnupriya Buggineni,
Cheng Chen,
Jaime Camelio
Abstract:Addressing the challenges of data scarcity and privacy, synthetic data generation offers an innovative solution that advances manufacturing assembly operations and data analytics. Serving as a viable alternative, it enables manufacturers to leverage a broader and more diverse range of machine learning models by incorporating the creation of artificial data points for training and evaluation. Current methods lack generalizable framework for researchers to follow and solve these issues. The development of synthe… Show more
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