Transfer of Process References between Machine Tools for Online Tool Condition Monitoring

Process and tool condition monitoring systems are a prerequisite for autonomous production. One approach to monitoring individual parts without complex cutting simulations is the transfer of knowledge among similar monitoring scenarios. This paper introduces a novel monitoring method which transfers...

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Autores principales:	Berend Denkena, Benjamin Bergmann, Tobias H. Stiehl
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	machine tools turning process monitoring knowledge transfer Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/8e5becade4af4eea846c016eb8b96721
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id	oai:doaj.org-article:8e5becade4af4eea846c016eb8b96721
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spelling	oai:doaj.org-article:8e5becade4af4eea846c016eb8b967212021-11-25T18:12:16ZTransfer of Process References between Machine Tools for Online Tool Condition Monitoring10.3390/machines91102822075-1702https://doaj.org/article/8e5becade4af4eea846c016eb8b967212021-11-01T00:00:00Zhttps://www.mdpi.com/2075-1702/9/11/282https://doaj.org/toc/2075-1702Process and tool condition monitoring systems are a prerequisite for autonomous production. One approach to monitoring individual parts without complex cutting simulations is the transfer of knowledge among similar monitoring scenarios. This paper introduces a novel monitoring method which transfers monitoring limits for process signals between different machine tools. The method calculates monitoring limits statistically from cutting processes carried out on one or more similar machines. The monitoring algorithm aims to detect general process anomalies online. Experiments comprise face-turning operations at five different lathes, four of which were of the same model. Results include the successful transfer of monitoring limits between machines of the same model for the detection of material anomalies. In comparison to an approach based on dynamic time warping (DTW) and density-based spatial clustering of applications with noise (DBSCAN), the new method showed fewer false alarms and higher detection rates. However, for the transfer between different models of machines, the successful application of the new method is limited. This is predominantly due to limitations of the employed process component isolation and differences between machine models in terms of signal properties as well as execution speed.Berend DenkenaBenjamin BergmannTobias H. StiehlMDPI AGarticlemachine toolsturningprocess monitoringknowledge transferMechanical engineering and machineryTJ1-1570ENMachines, Vol 9, Iss 282, p 282 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	machine tools turning process monitoring knowledge transfer Mechanical engineering and machinery TJ1-1570
spellingShingle	machine tools turning process monitoring knowledge transfer Mechanical engineering and machinery TJ1-1570 Berend Denkena Benjamin Bergmann Tobias H. Stiehl Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
description	Process and tool condition monitoring systems are a prerequisite for autonomous production. One approach to monitoring individual parts without complex cutting simulations is the transfer of knowledge among similar monitoring scenarios. This paper introduces a novel monitoring method which transfers monitoring limits for process signals between different machine tools. The method calculates monitoring limits statistically from cutting processes carried out on one or more similar machines. The monitoring algorithm aims to detect general process anomalies online. Experiments comprise face-turning operations at five different lathes, four of which were of the same model. Results include the successful transfer of monitoring limits between machines of the same model for the detection of material anomalies. In comparison to an approach based on dynamic time warping (DTW) and density-based spatial clustering of applications with noise (DBSCAN), the new method showed fewer false alarms and higher detection rates. However, for the transfer between different models of machines, the successful application of the new method is limited. This is predominantly due to limitations of the employed process component isolation and differences between machine models in terms of signal properties as well as execution speed.
format	article
author	Berend Denkena Benjamin Bergmann Tobias H. Stiehl
author_facet	Berend Denkena Benjamin Bergmann Tobias H. Stiehl
author_sort	Berend Denkena
title	Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
title_short	Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
title_full	Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
title_fullStr	Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
title_full_unstemmed	Transfer of Process References between Machine Tools for Online Tool Condition Monitoring
title_sort	transfer of process references between machine tools for online tool condition monitoring
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8e5becade4af4eea846c016eb8b96721
work_keys_str_mv	AT berenddenkena transferofprocessreferencesbetweenmachinetoolsforonlinetoolconditionmonitoring AT benjaminbergmann transferofprocessreferencesbetweenmachinetoolsforonlinetoolconditionmonitoring AT tobiashstiehl transferofprocessreferencesbetweenmachinetoolsforonlinetoolconditionmonitoring
_version_	1718411510287433728

Transfer of Process References between Machine Tools for Online Tool Condition Monitoring

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