Diagnosis of tool wear with a microcontroller

Erkki Jantunen; Eero Vaajoensuu

doi:10.3182/20060517-3-FR-2903.00012

Diagnosis of tool wear with a microcontroller

Erkki Jantunen^*
, Eero Vaajoensuu

^*Corresponding author for this work

VTT (former employee or external)

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

Tool wear monitoring is very important for economical reasons. In this paper a very economical solution is presented. The idea is to use easily available microcontroller based hardware, which is very cheap due to mass production. The cheap hardware is combined together with sophisticated software. The use of regression analysis techniques together with fuzzy logic in order to overcome the challenges in tool wear monitoring forms the basis of the developed approach. The proposed approach is tested with data from drilling tests.

Original language	English
Title of host publication	12th IFAC Symposium on Information Control Problems in Manufacturing
Publisher	Elsevier
Pages	15-20
ISBN (Print)	978-3-902661-04-3
DOIs	https://doi.org/10.3182/20060517-3-FR-2903.00012
Publication status	Published - 1 Dec 2006
MoE publication type	A4 Article in a conference publication
Event	12th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2006, and Associated Industrial Meetings: EMM'2006, BPM'2006, JT'2006 - Saint - Etienne, France Duration: 17 May 2006 → 19 May 2006

Publication series

Series	IFAC Proceedings Volumes
Number	3
Volume	39
ISSN	1474-6670

Conference

Conference	12th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2006, and Associated Industrial Meetings: EMM'2006, BPM'2006, JT'2006
Country/Territory	France
City	Saint - Etienne
Period	17/05/06 → 19/05/06

Funding

This work is a part of a project Multiple INtelligent Diagnostics for MAchiNery (MindMan) funded by the Tekes (National Technology Agency of Finland) and industry Metso Paper, Rautaruukki Raahe Steel Works, Fläkt Woods Oy, Danisco Sweeteners, Oy Sinebrychoff Ab and HK Ruokatalo Oyj.

Keywords

Fuzzy logic
Microprocessor
Monitoring
Regression analysis
Signal analysis

Access to Document

10.3182/20060517-3-FR-2903.00012

Cite this

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title = "Diagnosis of tool wear with a microcontroller",

abstract = "Tool wear monitoring is very important for economical reasons. In this paper a very economical solution is presented. The idea is to use easily available microcontroller based hardware, which is very cheap due to mass production. The cheap hardware is combined together with sophisticated software. The use of regression analysis techniques together with fuzzy logic in order to overcome the challenges in tool wear monitoring forms the basis of the developed approach. The proposed approach is tested with data from drilling tests.",

keywords = "Fuzzy logic, Microprocessor, Monitoring, Regression analysis, Signal analysis",

author = "Erkki Jantunen and Eero Vaajoensuu",

year = "2006",

month = dec,

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doi = "10.3182/20060517-3-FR-2903.00012",

language = "English",

isbn = "978-3-902661-04-3",

series = "IFAC Proceedings Volumes",

publisher = "Elsevier",

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note = "12th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2006, and Associated Industrial Meetings: EMM'2006, BPM'2006, JT'2006 ; Conference date: 17-05-2006 Through 19-05-2006",

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Jantunen, E & Vaajoensuu, E 2006, Diagnosis of tool wear with a microcontroller. in 12th IFAC Symposium on Information Control Problems in Manufacturing. Elsevier, IFAC Proceedings Volumes, no. 3, vol. 39, pp. 15-20, 12th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2006, and Associated Industrial Meetings: EMM'2006, BPM'2006, JT'2006, Saint - Etienne, France, 17/05/06. https://doi.org/10.3182/20060517-3-FR-2903.00012

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AB - Tool wear monitoring is very important for economical reasons. In this paper a very economical solution is presented. The idea is to use easily available microcontroller based hardware, which is very cheap due to mass production. The cheap hardware is combined together with sophisticated software. The use of regression analysis techniques together with fuzzy logic in order to overcome the challenges in tool wear monitoring forms the basis of the developed approach. The proposed approach is tested with data from drilling tests.

KW - Fuzzy logic

KW - Microprocessor

KW - Monitoring

KW - Regression analysis

KW - Signal analysis

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Y2 - 17 May 2006 through 19 May 2006

ER -

Diagnosis of tool wear with a microcontroller

Abstract

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Conference

Funding

Keywords

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