Use of NC kernel data for surface roughness monitoring in milling operations.
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| Title: | Use of NC kernel data for surface roughness monitoring in milling operations. |
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| Authors: | Brecher, Christian1 c.brecher@wzl.rwth-aachen.de, Quintana, Guillem2 gquintana@ascamm.com, Rudolf, Thomas1 t.rudolf@wzl.rwth-aachen.de, Ciurana, Joaquim3 quim.ciurana@udg.edu |
| Source: | International Journal of Advanced Manufacturing Technology. Apr2011, Vol. 53 Issue 9-12, p953-962. 10p. 1 Color Photograph, 5 Diagrams, 1 Chart, 4 Graphs. |
| Subjects: | Programming of numerically controlled machine tools, Surface roughness, Kernel functions, Data analysis, Milling (Metalwork), Operations research, Information processing, Human-machine systems |
| Abstract: | This work focuses on developing an application based on the information contained in the numerical control (NC) kernel for surface roughness monitoring of the part in process. A human-machine interface (HMI) was developed in order to facilitate the interaction between the operator and the NC kernel with a graphical user interface working in the computer numerically controlled (CNC) screen. Experimentation was carried out in order to obtain the data to be modeled with artificial neural networks for surface roughness average parameter (Ra) predictions. Finally, a compact solution was implemented through global user data (GUD). Data from the HMI and from the kernel are collected in the GUD and analyzed with the artificial neural network. The application provides the surface roughness average parameter of the part in process and gives optimized parameters to the operator. Verification tests were carried out, showing accurate results. The use of the application developed in this research ensures the surface roughness Ra requirement, improves cutting parameters, reduces manual finishing operations and unacceptable parts at the end of the manufacturing process, and provides a solution implemented in the machine tool CNC screen without the need of any other external sensors. [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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 59341837 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Use of NC kernel data for surface roughness monitoring in milling operations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Brecher%2C+Christian%22">Brecher, Christian</searchLink><relatesTo>1</relatesTo><i> c.brecher@wzl.rwth-aachen.de</i><br /><searchLink fieldCode="AR" term="%22Quintana%2C+Guillem%22">Quintana, Guillem</searchLink><relatesTo>2</relatesTo><i> gquintana@ascamm.com</i><br /><searchLink fieldCode="AR" term="%22Rudolf%2C+Thomas%22">Rudolf, Thomas</searchLink><relatesTo>1</relatesTo><i> t.rudolf@wzl.rwth-aachen.de</i><br /><searchLink fieldCode="AR" term="%22Ciurana%2C+Joaquim%22">Ciurana, Joaquim</searchLink><relatesTo>3</relatesTo><i> quim.ciurana@udg.edu</i> – 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>. Apr2011, Vol. 53 Issue 9-12, p953-962. 10p. 1 Color Photograph, 5 Diagrams, 1 Chart, 4 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Programming+of+numerically+controlled+machine+tools%22">Programming of numerically controlled machine tools</searchLink><br /><searchLink fieldCode="DE" term="%22Surface+roughness%22">Surface roughness</searchLink><br /><searchLink fieldCode="DE" term="%22Kernel+functions%22">Kernel functions</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Milling+%28Metalwork%29%22">Milling (Metalwork)</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Information+processing%22">Information processing</searchLink><br /><searchLink fieldCode="DE" term="%22Human-machine+systems%22">Human-machine systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This work focuses on developing an application based on the information contained in the numerical control (NC) kernel for surface roughness monitoring of the part in process. A human-machine interface (HMI) was developed in order to facilitate the interaction between the operator and the NC kernel with a graphical user interface working in the computer numerically controlled (CNC) screen. Experimentation was carried out in order to obtain the data to be modeled with artificial neural networks for surface roughness average parameter (Ra) predictions. Finally, a compact solution was implemented through global user data (GUD). Data from the HMI and from the kernel are collected in the GUD and analyzed with the artificial neural network. The application provides the surface roughness average parameter of the part in process and gives optimized parameters to the operator. Verification tests were carried out, showing accurate results. The use of the application developed in this research ensures the surface roughness Ra requirement, improves cutting parameters, reduces manual finishing operations and unacceptable parts at the end of the manufacturing process, and provides a solution implemented in the machine tool CNC screen without the need of any other external sensors. [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/s00170-010-2904-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 953 Subjects: – SubjectFull: Programming of numerically controlled machine tools Type: general – SubjectFull: Surface roughness Type: general – SubjectFull: Kernel functions Type: general – SubjectFull: Data analysis Type: general – SubjectFull: Milling (Metalwork) Type: general – SubjectFull: Operations research Type: general – SubjectFull: Information processing Type: general – SubjectFull: Human-machine systems Type: general Titles: – TitleFull: Use of NC kernel data for surface roughness monitoring in milling operations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Brecher, Christian – PersonEntity: Name: NameFull: Quintana, Guillem – PersonEntity: Name: NameFull: Rudolf, Thomas – PersonEntity: Name: NameFull: Ciurana, Joaquim IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 02683768 Numbering: – Type: volume Value: 53 – Type: issue Value: 9-12 Titles: – TitleFull: International Journal of Advanced Manufacturing Technology Type: main |
| ResultId | 1 |
