Academic Journal
Simulation-Assisted Prediction of Surface Topography for Milling Strategy Selection in Freeform 3-Axis and 5-Axis Ball-End Milling.
| Τίτλος: | Simulation-Assisted Prediction of Surface Topography for Milling Strategy Selection in Freeform 3-Axis and 5-Axis Ball-End Milling. |
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| Συγγραφείς: | Frechilla, Alejandro, Zekalmi, Yasser, Albajez, José Antonio, Oliveros, María José, Aguado, Sergio |
| Πηγή: | Journal of Manufacturing & Materials Processing; Sep2026, Vol. 10 Issue 9, p334, 28p |
| Θεματικοί όροι: | Surface topography, Frequency-domain analysis, Prediction algorithms, Surface texture, Curved surfaces, Milling-machines, Machining |
| Περίληψη: | Surface topography plays a critical role in the functional performance of machined freeform components, yet its assessment traditionally takes place only after manufacturing. This work presents a simulation-assisted framework for predicting the surface topography generated during freeform ball-end milling and using these predictions to support machining-strategy selection. Three finishing strategies (3-axis square, SQ3, 3-axis spiral, SP3, and 5-axis spiral, SP5) were investigated on a representative freeform benchmark by combining high-resolution UVRMAP simulations with experimental topography measurements. Surface signatures were characterized using ISO 25178 areal parameters together with two- and one-dimensional Fast Fourier Transform (FFT) analyses, enabling quantitative evaluation of surface amplitude, preferential orientations, anisotropy, and characteristic spatial periodicities. The results demonstrate that machining strategy and local surface geometry produce distinctive topographical signatures that cannot be fully described by conventional roughness parameters alone.Theproposed UVRMAP methodology accurately reproduces the primary spatial organization of the geometric texture generated by the programmed toolpath, while the incorporation of a controlled non-ideal cutter-edge representation improves the prediction of experimentally observed fine-scale features. The combined experimental–simulation methodology provides a robust framework for comparing and validating the spatial and morphological characteristics of predicted surface topographies, providing a basis for future machining-strategy selection according to application-specific surface requirements. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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| Header | DbId: edb DbLabel: Complementary Index An: 197429964 RelevancyScore: 1082 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1082.42749023438 |
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| Items | – Name: Title Label: Title Group: Ti Data: Simulation-Assisted Prediction of Surface Topography for Milling Strategy Selection in Freeform 3-Axis and 5-Axis Ball-End Milling. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Frechilla%2C+Alejandro%22">Frechilla, Alejandro</searchLink><br /><searchLink fieldCode="AR" term="%22Zekalmi%2C+Yasser%22">Zekalmi, Yasser</searchLink><br /><searchLink fieldCode="AR" term="%22Albajez%2C+José+Antonio%22">Albajez, José Antonio</searchLink><br /><searchLink fieldCode="AR" term="%22Oliveros%2C+María+José%22">Oliveros, María José</searchLink><br /><searchLink fieldCode="AR" term="%22Aguado%2C+Sergio%22">Aguado, Sergio</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Manufacturing & Materials Processing; Sep2026, Vol. 10 Issue 9, p334, 28p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Surface+topography%22">Surface topography</searchLink><br /><searchLink fieldCode="DE" term="%22Frequency-domain+analysis%22">Frequency-domain analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+algorithms%22">Prediction algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Surface+texture%22">Surface texture</searchLink><br /><searchLink fieldCode="DE" term="%22Curved+surfaces%22">Curved surfaces</searchLink><br /><searchLink fieldCode="DE" term="%22Milling-machines%22">Milling-machines</searchLink><br /><searchLink fieldCode="DE" term="%22Machining%22">Machining</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Surface topography plays a critical role in the functional performance of machined freeform components, yet its assessment traditionally takes place only after manufacturing. This work presents a simulation-assisted framework for predicting the surface topography generated during freeform ball-end milling and using these predictions to support machining-strategy selection. Three finishing strategies (3-axis square, SQ3, 3-axis spiral, SP3, and 5-axis spiral, SP5) were investigated on a representative freeform benchmark by combining high-resolution UVRMAP simulations with experimental topography measurements. Surface signatures were characterized using ISO 25178 areal parameters together with two- and one-dimensional Fast Fourier Transform (FFT) analyses, enabling quantitative evaluation of surface amplitude, preferential orientations, anisotropy, and characteristic spatial periodicities. The results demonstrate that machining strategy and local surface geometry produce distinctive topographical signatures that cannot be fully described by conventional roughness parameters alone.Theproposed UVRMAP methodology accurately reproduces the primary spatial organization of the geometric texture generated by the programmed toolpath, while the incorporation of a controlled non-ideal cutter-edge representation improves the prediction of experimentally observed fine-scale features. The combined experimental–simulation methodology provides a robust framework for comparing and validating the spatial and morphological characteristics of predicted surface topographies, providing a basis for future machining-strategy selection according to application-specific surface requirements. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Manufacturing & Materials Processing is the property of MDPI 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: 10.3390/jmmp10090334 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 28 StartPage: 334 Subjects: – SubjectFull: Surface topography Type: general – SubjectFull: Frequency-domain analysis Type: general – SubjectFull: Prediction algorithms Type: general – SubjectFull: Surface texture Type: general – SubjectFull: Curved surfaces Type: general – SubjectFull: Milling-machines Type: general – SubjectFull: Machining Type: general Titles: – TitleFull: Simulation-Assisted Prediction of Surface Topography for Milling Strategy Selection in Freeform 3-Axis and 5-Axis Ball-End Milling. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Frechilla, Alejandro – PersonEntity: Name: NameFull: Zekalmi, Yasser – PersonEntity: Name: NameFull: Albajez, José Antonio – PersonEntity: Name: NameFull: Oliveros, María José – PersonEntity: Name: NameFull: Aguado, Sergio IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 25044494 Numbering: – Type: volume Value: 10 – Type: issue Value: 9 Titles: – TitleFull: Journal of Manufacturing & Materials Processing Type: main |
| ResultId | 1 |