Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection

Zhicheng Xu; Wai Sze Yip; Suet To

doi:10.1016/j.procir.2023.04.012

Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection

Zhicheng Xu, Wai Sze Yip, Suet To (Corresponding Author)

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation for subsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finally employed and validated on a three-axis ultra-precision milling machine tool. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals.

Original language	English
Title of host publication	The 33rd CIRP Design Conference
Pages	1210-1215
Number of pages	6
Volume	119
DOIs	https://doi.org/10.1016/j.procir.2023.04.012
Publication status	Published - Jul 2023
Event	33rd CIRP Design Conference - Sydney, Australia Duration: 17 May 2023 → 19 May 2023 https://www.cirpdesign2023.com/

Publication series

Name	Procedia CIRP
Publisher	Elsevier BV
ISSN (Print)	2212-8271

Conference

Conference	33rd CIRP Design Conference
Country/Territory	Australia
City	Sydney
Period	17/05/23 → 19/05/23
Internet address	https://www.cirpdesign2023.com/

Keywords

Anomaly detection
Condition monitoring
Ultra-precision machining

ASJC Scopus subject areas

Control and Systems Engineering
Industrial and Manufacturing Engineering

More information

10.1016/j.procir.2023.04.012

http://hdl.handle.net/10397/108519

Cite this

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title = "Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection",

abstract = "Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation for subsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finally employed and validated on a three-axis ultra-precision milling machine tool. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals.",

keywords = "Anomaly detection, Condition monitoring, Ultra-precision machining",

author = "Zhicheng Xu and Yip, {Wai Sze} and Suet To",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0); 33rd CIRP Design Conference ; Conference date: 17-05-2023 Through 19-05-2023",

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doi = "10.1016/j.procir.2023.04.012",

language = "English",

volume = "119",

series = "Procedia CIRP",

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Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection. / Xu, Zhicheng; Yip, Wai Sze ; To, Suet (Corresponding Author).
The 33rd CIRP Design Conference. Vol. 119 2023. p. 1210-1215 (Procedia CIRP).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection

AU - Xu, Zhicheng

AU - Yip, Wai Sze

AU - To, Suet

PY - 2023/7

Y1 - 2023/7

N2 - Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation for subsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finally employed and validated on a three-axis ultra-precision milling machine tool. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals.

AB - Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation for subsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finally employed and validated on a three-axis ultra-precision milling machine tool. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals.

KW - Anomaly detection

KW - Condition monitoring

KW - Ultra-precision machining

UR - http://www.scopus.com/inward/record.url?scp=85169923061&partnerID=8YFLogxK

U2 - 10.1016/j.procir.2023.04.012

DO - 10.1016/j.procir.2023.04.012

M3 - Conference article published in proceeding or book

AN - SCOPUS:85169923061

VL - 119

T3 - Procedia CIRP

SP - 1210

EP - 1215

BT - The 33rd CIRP Design Conference

T2 - 33rd CIRP Design Conference

Y2 - 17 May 2023 through 19 May 2023

ER -

Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

More information

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