Tensor Data Analytics in Advanced Manufacturing Processes

Bo Shen ()
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Bo Shen: New Jersey Institute of Technology

A chapter in Multimodal and Tensor Data Analytics for Industrial Systems Improvement, 2024, pp 107-121 from Springer

Abstract: Abstract The emergence of edge computing, coupled with the growth of the Industrial Internet of Things (IIoT), along with sensors and intelligent/smart technologies, has opened up significant possibilities for the progression of advanced manufacturing. Together with data science and artificial intelligence, manufacturing data analytics are transforming manufacturing from limited factory floor automation to fully autonomous and interconnected systems. These data analytics methods are mainly based on vectors; however, real-world manufacturing data are presented in the format of high-order tensors. Accordingly, tensor data analytics has become a fast-growing area for advanced manufacturing. In this chapter, two robust tensor decomposition methods, motivated by specific engineering problems, are introduced for process monitoring in metal additive manufacturing.

Keywords: Robust tensor decomposition; Smooth sparse decomposition; Advanced manufacturing (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-53092-0_6

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