Evaluation of slot milling processes on carbon fiber reinforced polyetheretherketone thermoplastic composite utilizing nanofluid-enhanced minimum quantity lubrication technique

Sanctions aimed at reducing carbon emissions promote the adoption of sustainable materials, such as carbon fiber-reinforced polyetheretherketone (CF/PEEK) thermoplastic composites, in the aerospace sector due to their distinctive characteristics. The application of the secondary machining used in the production of functional components from CF/PEEK composite material in dry and wet cutting conditions causes performance and efficiency loss on the material and process. Therefore, in this study, the minimum quantity lubrication (MQL) and MQL using the multi-walled carbon nanotube-reinforced nanofluid (N-MQL) techniques were utilized for the first time in the milling of CF/PEEK, and the machining performance was evaluated in terms of cutting force, feed force, cutting temperature, surface roughness, surface topography, burr height, and dimensional error. In comparison to dry cutting, the N-MQL method achieved maximum improvements of 77.5%, 71.8%, 67.5%, 49.4%, 71.8%, 74.1%, and 90.4% in these machining outputs, respectively. Then, the optimum cutting parameters considering all machining responses were selected using TOPSIS, VIKOR, CoCoSo, and MOORA multi-criteria decision-making (MCDM) methods. MCDM results showed that to obtain optimum machining responses in CF/PEEK machining, the N-MQL cutting condition should be used as well as the low/average cutting speed and low feed values.

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Publication Details

Journal
Journal of Thermoplastic Composite Materials
Published
2025-05-19
DOI
https://doi.org/10.1177/08927057251344136
Citations
6
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
4.28

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article

Evaluation of slot milling processes on carbon fiber reinforced polyetheretherketone thermoplastic composite utilizing nanofluid-enhanced minimum quantity lubrication technique

Elvan Ateş, Alper Uysal, Yusuf Furkan Yapan, Yunus Yavuz et al.
6 citations
Journal of Thermoplastic Composite Materials
Advanced machining processes and optimization
4.28
article

Evaluation of slot milling processes on carbon fiber reinforced polyetheretherketone thermoplastic composite utilizing nanofluid-enhanced minimum quantity lubrication technique

Elvan Ateş, Alper Uysal, Yusuf Furkan Yapan, Yunus Yavuz, Mutlu Özcan, Görkem ÖZTÜRK, Kemal Vahapoğlu, Enes Çifci
article en
6 citations

Abstract

Sanctions aimed at reducing carbon emissions promote the adoption of sustainable materials, such as carbon fiber-reinforced polyetheretherketone (CF/PEEK) thermoplastic composites, in the aerospace sector due to their distinctive characteristics. The application of the secondary machining used in the production of functional components from CF/PEEK composite material in dry and wet cutting conditions causes performance and efficiency loss on the material and process. Therefore, in this study, the minimum quantity lubrication (MQL) and MQL using the multi-walled carbon nanotube-reinforced nanofluid (N-MQL) techniques were utilized for the first time in the milling of CF/PEEK, and the machining performance was evaluated in terms of cutting force, feed force, cutting temperature, surface roughness, surface topography, burr height, and dimensional error. In comparison to dry cutting, the N-MQL method achieved maximum improvements of 77.5%, 71.8%, 67.5%, 49.4%, 71.8%, 74.1%, and 90.4% in these machining outputs, respectively. Then, the optimum cutting parameters considering all machining responses were selected using TOPSIS, VIKOR, CoCoSo, and MOORA multi-criteria decision-making (MCDM) methods. MCDM results showed that to obtain optimum machining responses in CF/PEEK machining, the N-MQL cutting condition should be used as well as the low/average cutting speed and low feed values.

Journal of Thermoplastic Composite MaterialsVol. 38(11)
Yıldız Technical University (TR), Turkish Aerospace Industries (Turkey) (TR)
Türk Havacılık ve Uzay Sanayii
Openalex Percentile: Top 6%
Advanced machining processes and optimization
4.28
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