Diagnosis of tool wear with a microcontroller

Erkki Jantunen, Eero Vaajoensuu

    Research output: Contribution to journalArticleScientificpeer-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 languageEnglish
    Pages (from-to)15-20
    JournalIFAC Proceedings Volumes
    Volume39
    Issue number3
    DOIs
    Publication statusPublished - 1 Dec 2006
    MoE publication typeA1 Journal article-refereed
    Event12th 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 200619 May 2006

    Fingerprint

    Microcontrollers
    Wear of materials
    Hardware
    Monitoring
    Regression analysis
    Fuzzy logic
    Drilling

    Keywords

    • Fuzzy logic
    • Microprocessor
    • Monitoring
    • Regression analysis
    • Signal analysis

    Cite this

    Jantunen, Erkki ; Vaajoensuu, Eero. / Diagnosis of tool wear with a microcontroller. In: IFAC Proceedings Volumes. 2006 ; Vol. 39, No. 3. pp. 15-20.
    @article{d592dc79229143c5960e5568194087f7,
    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 = "12",
    day = "1",
    doi = "10.3182/20060517-3-FR-2903.00012",
    language = "English",
    volume = "39",
    pages = "15--20",
    journal = "IFAC-PapersOnLine",
    issn = "2405-8971",
    publisher = "IFAC Secretariat",
    number = "3",

    }

    Diagnosis of tool wear with a microcontroller. / Jantunen, Erkki; Vaajoensuu, Eero.

    In: IFAC Proceedings Volumes, Vol. 39, No. 3, 01.12.2006, p. 15-20.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Diagnosis of tool wear with a microcontroller

    AU - Jantunen, Erkki

    AU - Vaajoensuu, Eero

    PY - 2006/12/1

    Y1 - 2006/12/1

    N2 - 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.

    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

    UR - http://www.scopus.com/inward/record.url?scp=79961175438&partnerID=8YFLogxK

    U2 - 10.3182/20060517-3-FR-2903.00012

    DO - 10.3182/20060517-3-FR-2903.00012

    M3 - Article

    AN - SCOPUS:79961175438

    VL - 39

    SP - 15

    EP - 20

    JO - IFAC-PapersOnLine

    JF - IFAC-PapersOnLine

    SN - 2405-8971

    IS - 3

    ER -