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- Title
Multi-source transfer learning of time series in cyclical manufacturing.
- Authors
Zellinger, Werner; Grubinger, Thomas; Zwick, Michael; Lughofer, Edwin; Schöner, Holger; Natschläger, Thomas; Saminger-Platz, Susanne
- Abstract
This paper describes a new transfer learning method for modeling sensor time series following multiple different distributions, e.g. originating from multiple different tool settings. The method aims at removing distribution specific information before the modeling of the individual time series takes place. This is done by mapping the data to a new space such that the representations of different distributions are aligned. Domain knowledge is incorporated by means of corresponding parameters, e.g. physical dimensions of tool settings. Results on a real-world problem of industrial manufacturing show that our method is able to significantly improve the performance of regression models on time series following previously unseen distributions.
- Subjects
INFORMATION modeling; REGRESSION analysis; DATA mapping; MANUFACTURING processes; TIME series analysis
- Publication
Journal of Intelligent Manufacturing, 2020, Vol 31, Issue 3, p777
- ISSN
0956-5515
- Publication type
Academic Journal
- DOI
10.1007/s10845-019-01499-4