Tensor Data Analytics in Advanced Manufacturing Processes

Document Type

Syllabus

Publication Date

1-1-2024

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.

Identifier

85194578269 (Scopus)

Publication Title

Springer Optimization and Its Applications

External Full Text Location

https://doi.org/10.1007/978-3-031-53092-0_6

e-ISSN

19316836

ISSN

19316828

First Page

107

Last Page

121

Volume

211

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