State-of-the-art methods and results in tool condition monitoring: a review.
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| Title: | State-of-the-art methods and results in tool condition monitoring: a review. |
|---|---|
| Authors: | Rehorn, Adam G.1,2 adam.rehorn@nrc.gc.ca, Jin Jiang1, Orban, Peter E.2 |
| Source: | International Journal of Advanced Manufacturing Technology. Oct2005, Vol. 26 Issue 7/8, p693-710. 18p. |
| Subjects: | Machine tool monitoring, Detectors, Signal processing, Milling (Metalwork), Cutting (Materials) |
| Abstract: | This paper presents a review of the state-of-the-art in sensors and signal processing methodologies used for tool condition monitoring (TCM) systems in industrial machining applications. The paper focuses on the technologies used in monitoring conventional cutting operations, including drilling, turning, end milling and face milling, and presents important findings related to each of these fields. Unlike existing reviews, which categorize results according to the methodology used, this paper presents results organized according to the type of machining operation carried out. By extensively reviewing and categorizing over one hundred important papers and articles, this paper is able to identify and comment on trends in TCM research, and to identify potential weaknesses in certain areas. The paper concludes with a list of recommendations for future research based on the trends and successful results observed, thus facilitating the cross-fertilization of ideas and techniques within the field of TCM research. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 18522734 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: State-of-the-art methods and results in tool condition monitoring: a review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rehorn%2C+Adam+G%2E%22">Rehorn, Adam G.</searchLink><relatesTo>1,2</relatesTo><i> adam.rehorn@nrc.gc.ca</i><br /><searchLink fieldCode="AR" term="%22Jin+Jiang%22">Jin Jiang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Orban%2C+Peter+E%2E%22">Orban, Peter E.</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Advanced+Manufacturing+Technology%22">International Journal of Advanced Manufacturing Technology</searchLink>. Oct2005, Vol. 26 Issue 7/8, p693-710. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Machine+tool+monitoring%22">Machine tool monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Detectors%22">Detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Milling+%28Metalwork%29%22">Milling (Metalwork)</searchLink><br /><searchLink fieldCode="DE" term="%22Cutting+%28Materials%29%22">Cutting (Materials)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents a review of the state-of-the-art in sensors and signal processing methodologies used for tool condition monitoring (TCM) systems in industrial machining applications. The paper focuses on the technologies used in monitoring conventional cutting operations, including drilling, turning, end milling and face milling, and presents important findings related to each of these fields. Unlike existing reviews, which categorize results according to the methodology used, this paper presents results organized according to the type of machining operation carried out. By extensively reviewing and categorizing over one hundred important papers and articles, this paper is able to identify and comment on trends in TCM research, and to identify potential weaknesses in certain areas. The paper concludes with a list of recommendations for future research based on the trends and successful results observed, thus facilitating the cross-fertilization of ideas and techniques within the field of TCM research. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00170-004-2038-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 693 Subjects: – SubjectFull: Machine tool monitoring Type: general – SubjectFull: Detectors Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Milling (Metalwork) Type: general – SubjectFull: Cutting (Materials) Type: general Titles: – TitleFull: State-of-the-art methods and results in tool condition monitoring: a review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rehorn, Adam G. – PersonEntity: Name: NameFull: Jin Jiang – PersonEntity: Name: NameFull: Orban, Peter E. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2005 Type: published Y: 2005 Identifiers: – Type: issn-print Value: 02683768 Numbering: – Type: volume Value: 26 – Type: issue Value: 7/8 Titles: – TitleFull: International Journal of Advanced Manufacturing Technology Type: main |
| ResultId | 1 |
