Digital twin approach for tool wear monitoring of micro-milling

Gandjar Kiswanto; Ario Sunar Baskoro

doi:10.1016/j.procir.2020.03.140

Digital twin approach for tool wear monitoring of micro-milling

Gandjar Kiswanto, Ario Sunar Baskoro

Department of Mechanical Engineering

Research output: Contribution to journal › Conference article › peer-review

31 Citations (Scopus)

Abstract

This paper presents a novel implementation of digital twin (DT) technology in monitoring the wear condition of micro tool (TWM) during micro-milling process. The proposed DT is capable to predict the wear condition of micro tool using electric current data of spindle motor. This minimal setup of the system gives potential benefits for various deployment in real industrial practice. A miniaturized 5-axis micro-milling machine was used in the experiment to perform slot milling in micro-meter level. The proposed DT shows promising result of TCM in micro-milling within Industry 4.0 framework.

Original language	English
Pages (from-to)	1532-1537
Number of pages	6
Journal	Procedia CIRP
Volume	93
DOIs	https://doi.org/10.1016/j.procir.2020.03.140
Publication status	Published - 2020
Event	53rd CIRP Conference on Manufacturing Systems, CMS 2020 - Chicago, United States Duration: 1 Jul 2020 → 3 Jul 2020

Keywords

Digital twin
Industry 4.0
Micro-milling
Tool wear monitoring

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10.1016/j.procir.2020.03.140

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title = "Digital twin approach for tool wear monitoring of micro-milling",

abstract = "This paper presents a novel implementation of digital twin (DT) technology in monitoring the wear condition of micro tool (TWM) during micro-milling process. The proposed DT is capable to predict the wear condition of micro tool using electric current data of spindle motor. This minimal setup of the system gives potential benefits for various deployment in real industrial practice. A miniaturized 5-axis micro-milling machine was used in the experiment to perform slot milling in micro-meter level. The proposed DT shows promising result of TCM in micro-milling within Industry 4.0 framework.",

keywords = "Digital twin, Industry 4.0, Micro-milling, Tool wear monitoring",

author = "Gandjar Kiswanto and Baskoro, {Ario Sunar}",

note = "Funding Information: This research was partly supported by Beasiswa Pendidikan Indonesia from Indonesia Endowment Fund for Education (LPDP). Publisher Copyright: {\textcopyright} 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 53rd CIRP Conference on Manufacturing Systems; 53rd CIRP Conference on Manufacturing Systems, CMS 2020 ; Conference date: 01-07-2020 Through 03-07-2020",

year = "2020",

doi = "10.1016/j.procir.2020.03.140",

language = "English",

volume = "93",

pages = "1532--1537",

journal = "Procedia CIRP",

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T1 - Digital twin approach for tool wear monitoring of micro-milling

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AU - Baskoro, Ario Sunar

N1 - Funding Information: This research was partly supported by Beasiswa Pendidikan Indonesia from Indonesia Endowment Fund for Education (LPDP). Publisher Copyright: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 53rd CIRP Conference on Manufacturing Systems

PY - 2020

Y1 - 2020

N2 - This paper presents a novel implementation of digital twin (DT) technology in monitoring the wear condition of micro tool (TWM) during micro-milling process. The proposed DT is capable to predict the wear condition of micro tool using electric current data of spindle motor. This minimal setup of the system gives potential benefits for various deployment in real industrial practice. A miniaturized 5-axis micro-milling machine was used in the experiment to perform slot milling in micro-meter level. The proposed DT shows promising result of TCM in micro-milling within Industry 4.0 framework.

AB - This paper presents a novel implementation of digital twin (DT) technology in monitoring the wear condition of micro tool (TWM) during micro-milling process. The proposed DT is capable to predict the wear condition of micro tool using electric current data of spindle motor. This minimal setup of the system gives potential benefits for various deployment in real industrial practice. A miniaturized 5-axis micro-milling machine was used in the experiment to perform slot milling in micro-meter level. The proposed DT shows promising result of TCM in micro-milling within Industry 4.0 framework.

KW - Digital twin

KW - Industry 4.0

KW - Micro-milling

KW - Tool wear monitoring

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DO - 10.1016/j.procir.2020.03.140

M3 - Conference article

AN - SCOPUS:85098724835

SN - 2212-8271

VL - 93

SP - 1532

EP - 1537

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 53rd CIRP Conference on Manufacturing Systems, CMS 2020

Y2 - 1 July 2020 through 3 July 2020

ER -

Digital twin approach for tool wear monitoring of micro-milling

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Keywords

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