Scopus
YÖKSİS DOI Eşleşti
SJR Q1
Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis
Measurement Journal of the International Measurement Confederation · Mayıs 2012
YÖKSİS Kayıtları
Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis
Measurement · 2012 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Optimisation of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the Taguchi and RSM methods
2016 ISSN: 02632241 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
Classification of vertebral column disorders and lumbar discs disease using attribute weighting algorithm with mean shift clustering
2016 ISSN: 02632241 SCI-Expanded
Prof. Dr. HASAN ERDİNÇ KOÇER →
Point cloud filtering on UAV based point cloud
2019 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. MUSTAFA ZEYBEK →
Investigation of progressive tool wear for determining of optimized machining parameters in turning
2019 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. MUSTAFA KUNTOĞLU →
Analysis of effect factors on thermoelectric generator using Taguchi method
2020 ISSN: 0263-2241 SCI
Dr. Öğr. Üyesi HAKAN TERZİOĞLU →
Decomposition of process damping ratios and verification of process damping model for chatter vibration
2012 ISSN: 02632241 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis
2012 ISSN: 02632241 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
Optimization of tool geometry parameters for turning operations based on the response surface methodology
2011 ISSN: 02632241 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
A new process damping model for chatter vibration
2011 ISSN: 02632241 SCI-Expanded
Prof. Dr. SÜLEYMAN NEŞELİ →
Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning
2021 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. MUSTAFA KUNTOĞLU →
The determination of age and gender by implementing new image processing methods and measurements to dental X-ray images
2020 ISSN: 0263-2241 SCI-Expanded
Prof. Dr. FATİH BAŞÇİFTÇİ →
Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey
2021 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. MUSTAFA ZEYBEK →
Measuring curvature of trajectory traced by coupler of an optimal four-link spherical mechanism
2021 ISSN: 0263-2241 SCI-Expanded Q1
Dr. Öğr. Üyesi OSMAN ACAR →
A CNN-SVM Study Based on Selected Deep Features for Grapevine Leaves Classification
2022 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. MURAT KÖKLÜ →
An S-band zero-IF SFCW through-the-wall radar for range, respiration rate, and DOA estimation
2021 ISSN: 0263-2241 SCI-Expanded Q1
Prof. Dr. İSMAİL SARITAŞ →
An experimental study: Detecting the respiration rates of multiple stationary human targets by stepped frequency continuous wave radar
2021 ISSN: 0263-2241 SCI-Expanded Q1
Prof. Dr. İSMAİL SARITAŞ →
An experimental study: Detecting the respiration rates of multiple stationary human targets by stepped frequency continuous wave radar
2021 ISSN: 0263-2241 SCI-Expanded Q1
Dr. Öğr. Üyesi YUNUS EMRE ACAR →
An S-band zero-IF SFCW through-the-wall radar for range, respiration rate, and DOA estimation
2021 ISSN: 0263-2241 SCI-Expanded Q1
Dr. Öğr. Üyesi YUNUS EMRE ACAR →
A CNN-SVM study based on selected deep features for grapevine leaves classification
2022 ISSN: 0263-2241 SCI-Expanded Q1
Doç. Dr. İLKER ALİ ÖZKAN →
Advance monitoring of hole machining operations via intelligent measurement systems: A critical review and future trends
2022 ISSN: 0263-2241 SCI-Expanded Q1
Dr. Öğr. Üyesi ÜSAME ALİ USCA →
Makale Bilgileri
ISSN02632241
Yayın TarihiMayıs 2012
Cilt / Sayfa45 · 785-794
Scopus ID2-s2.0-84857451379
Özet
This study presents a new method to determine multi-objective optimal cutting conditions and mathematic models for surface roughness (Ra and Rz) on a CNC turning. Firstly, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. The AISI 304 austenitic stainless workpiece is machined by a coated carbide insert under dry conditions. The influence of cutting speed, feed rate and depth of cut on the surface roughness is examined. Secondly, the model for the surface roughness, as a function of cutting parameters, is obtained using the response surface methodology (RSM). Finally, the adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the feed rate is the dominant factor affecting surface roughness, which is minimized when the feed rate and depth of cut are set to the lowest level, while the cutting speed is set to the highest level. The percentages of error all fall within 1%, between the predicted values and the experimental values. This reveals that the prediction system established in this study produces satisfactory results, which are improved performance over other models in the literature. The enhanced method can be readily applied to different metal cutting processes with greater confidence. © 2012 Elsevier Ltd. All rights reserved.
Yazarlar (2)
1
İlhan Asiltürk
ORCID: 0000-0002-8302-6577
2
Süleyman Neşeli
Anahtar Kelimeler
DOE
Mathematical model
RSM
Surface roughness
Taguchi
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Son Atıflar
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Scimago Dergi (ISSN Eşleşmesi)
Measurement: Journal of the International Measurement Confederation
Q1
SJR Skoru1,244
H-Index146
YayıncıElsevier B.V.
ÜlkeNetherlands
Applied Mathematics (Q1)
Condensed Matter Physics (Q1)
Education (Q1)
Electrical and Electronic Engineering (Q1)
Instrumentation (Q1)
Statistics and Probability (Q1)
Metrikler
234
Atıf
2
Yazar
5
Anahtar Kelime