Modeling and multi response optimization of milling characteristics based on Taguchi and gray relational analysis
Yazarlar (3)
Prof. Dr. Murat SARIKAYA Sinop Üniversitesi, Türkiye
Volkan Yllmaz
Gazi Üniversitesi, Türkiye
Gazi Üniversitesi, Türkiye
Prof. Dr. Hakan Dilipak Gazi Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture (Q3) | ||
| Dergi ISSN | 0954-4054 Dergi Bilgileri (2016) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2016 |
| Cilt / Sayı / Sayfa | 230 / 6 / 1049–1065 | DOI | 10.1177/0954405414565136 |
| Makale Linki | http://pib.sagepub.com/lookup/doi/10.1177/0954405414565136 | ||
| UAK Araştırma Alanları |
Üretim Teknolojileri
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| Özet |
| This article focuses on experimental investigation and effective approach to optimize the milling characteristics with mono and multiple response outputs such as vibration signals, cutting force, and surface roughness. To achieve this goal, experiments were designed based on Taguchi’s L18 (21 × 33) orthogonal array. During the milling of AISI 1050 steel, process performance indicators such as vibration signals (RMS), cutting force (Fx), and surface roughness (Ra) were measured. The effect of process parameters such as depth of cut, feed rate, cutting speed, and number of insert on RMS, Fx, and Ra were investigated and parameters were simultaneously optimized by taking into consideration the multi-response outputs using Taguchi-based gray relational analysis. Taguchi’s signal-to-noise ratio was employed to obtain the best combination with smaller-the-better and larger-the-better approaches for mono- and … |
| Anahtar Kelimeler |
| Cutting | force | modeling | optimization | surfaces | vibration |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 41 |
| Scopus | 44 |
| Google Scholar | 62 |