ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

Big Data Analytics for Online Monitoring of Processes

12 September 2017, 16:00 – 16:20

Abstract

Submitted by
Flavia Dalia Frumosu
Authors
Flavia Dalia Frumosu (Technical University of Denmark), Murat Kulahci (Technical University of Denmark)
Abstract
The expanding availability of more complex data structures requires development of new analysis methods for process understanding and monitoring. The complex nature of the data is given by readily available high frequency and high dimensional data. There has been a considerable effort in incorporating latent structure based methods in the context of complex data. On the other hand, machine learning methods have received less focus as they have been primarily used for predictive objectives. In this paper we will explore through examples the use of machine learning methods further mentioned as big data analytics in the pursuit of process monitoring and control.
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