Computational methods for the detection of wear and damage to milling tools br

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Computational methods for the detection of wear and damage to milling tools br. / Ninevski, Dimitar; Thaler, Julia; O'Leary, Paul et al.
In: JOURNAL OF MANUFACTURING PROCESSES, Vol. 82, 10.2022, p. 78-87.

Research output: Contribution to journalArticleResearchpeer-review

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Ninevski D, Thaler J, O'Leary P, Klunsner T, Mucke M, Hanna L et al. Computational methods for the detection of wear and damage to milling tools br. JOURNAL OF MANUFACTURING PROCESSES. 2022 Oct;82:78-87. doi: 10.1016/j.jmapro.2022.07.030

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Bibtex - Download

@article{e1ff56d634ac481f97b1584cda6e9b06,
title = "Computational methods for the detection of wear and damage to milling tools br",
keywords = "Condition monitoring, Milling tool damage, Time-series sensor data",
author = "Dimitar Ninevski and Julia Thaler and Paul O'Leary and Thomas Klunsner and Manfred Mucke and Lukas Hanna and Tamara Teppernegg and Martin Treichler and Patrick Peissl and Christoph Czettl",
year = "2022",
month = oct,
doi = "10.1016/j.jmapro.2022.07.030",
language = "English",
volume = "82",
pages = "78--87",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Computational methods for the detection of wear and damage to milling tools br

AU - Ninevski, Dimitar

AU - Thaler, Julia

AU - O'Leary, Paul

AU - Klunsner, Thomas

AU - Mucke, Manfred

AU - Hanna, Lukas

AU - Teppernegg, Tamara

AU - Treichler, Martin

AU - Peissl, Patrick

AU - Czettl, Christoph

PY - 2022/10

Y1 - 2022/10

KW - Condition monitoring

KW - Milling tool damage

KW - Time-series sensor data

U2 - 10.1016/j.jmapro.2022.07.030

DO - 10.1016/j.jmapro.2022.07.030

M3 - Article

VL - 82

SP - 78

EP - 87

JO - JOURNAL OF MANUFACTURING PROCESSES

JF - JOURNAL OF MANUFACTURING PROCESSES

SN - 1526-6125

ER -