Multi response Optimization of Minimum Quantity Lubrication Parameters using Taguchi based Grey Relational Analysis in Turning of Difficult to cut Alloy Haynes 25
Yazarlar (2)
Prof. Dr. Murat SARIKAYA Sinop Üniversitesi, Türkiye
Öğr. Gör. Abdulkadir Güllü Gazi Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Journal of Cleaner Production (Q1)
Dergi ISSN 0959-6526 Dergi Bilgileri (2015)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 03-2015
Cilt / Sayı / Sayfa 91 / 1 / 347–357 DOI 10.1016/j.jclepro.2014.12.020
Makale Linki http://linkinghub.elsevier.com/retrieve/pii/S0959652614013092
UAK Araştırma Alanları
Üretim Teknolojileri
Özet
In manufacturing industry, the effect of cutting fluids has been known on the health, environment and productivity in machining operations such as turning, milling, drilling, etc. Minimum Quantity Lubrication (MQL) is an effective tool to minimize the damage of cutting fluids on health and environment in cutting processes. Thus, optimal process parameters must be determined under MQL cooling/lubrication condition to determine the maximum productivity. This paper presents an approach for optimization of machining parameters with multi-response outputs using design of experiment in turning. For experimental design, tests were planned based on Taguchi's L9 orthogonal array. During the turning of cobalt base super alloy Haynes 25 which is a difficult-to-cut material, process performance indicators such as flank wear, notch wear and surface roughness were measured. The process parameters which are cutting …
Anahtar Kelimeler
Cleaner production | Difficult-to-cut material | Grey relational analysis | Minimum quantity lubrication | Multi-response optimization