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2023 | OriginalPaper | Chapter

Multivariate Synchronization of NC Process Data Sets Based on Dynamic Time Warping

Authors : J. Ochel, M. Fey, C. Brecher

Published in: Production at the Leading Edge of Technology

Publisher: Springer International Publishing

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Abstract

Various sensors as well as the numeric control serve as sources for the acquisition of process data in operating machine tools. Since the manufacturing industry acknowledges the value immanent to the data, numerous approaches to analyze and exploit large amounts of data have been developed. Generating comparable data sets represents a general challenge when collecting data in real production environments. Multiple external interferences, such as interventions by the operator, alter the manufacturing process and the data set. In order to ensure the transferability of results, a standardized preprocessing and the comparability of data sets, such interferences need to be eliminated by a synchronization algorithm. In this paper, a novel approach is presented, which allows for a synchronization of numeric control process data sets considering multivariate raw data. The approach is able to align data sets of different lengths considering local process modifications. Reliably synchronizing data sets, the presented algorithm aims to support data preprocessing in manufacturing environments and, thus, facilitates the application of data-driven solutions for production optimization.

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Title: Multivariate Synchronization of NC Process Data Sets Based on Dynamic Time Warping
Authors: J. Ochel
M. Fey
C. Brecher
Publisher: Springer International Publishing
Book: Production at the Leading Edge of Technology
Print ISBN: 978-3-031-18317-1

Electronic ISBN: 978-3-031-18318-8

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-18318-8_30

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