Kurumun Atıf Alan Makalesi
Atıf Alan Yayın
Optimization of tool geometry parameters for turning operations based on the response surface methodology
Scopus
Toplam 237 atıf DOI
This investigation focuses on the influence of tool geometry on the surface finish obtained in turning of AISI 1040 steel. In order to find out the effect of tool geometry parameters on the surface roughness during turning, response surface methodology (RSM) was used and a prediction model was developed related to average surface roughness (Ra) using experimental data. The results indicated that the tool nose radius was the dominant factor on the surface roughness. In addition, a good agreement between the predicted and measured surface roughness was observed. Therefore, the developed model can be effectively used to predict the surface roughness on the machining of AISI 1040 steel with in 95% confidence intervals ranges of parameters studied. © 2010 Elsevier Ltd. All rights reserved.
Atıf Kaynağı
Atıf Yapan Yayın
Modeling of cutting parameters and tool geometry for multi-criteria optimization of surface roughness and vibration via response surface methodology in turning of AISI 5140 steel
Scopus
Havuzumuzda Open Access 119 atıf almış
AISI 5140 is a steel alloy used for manufacturing parts of medium speed and medium load such as gears and shafts mainly used in automotive applications. Parts made from AISI 5140 steel require machining processes such as turning and milling to achieve the final part shape. Limited research has been reported on the machining vibration and surface roughness during turning of AISI 5140 in the open literature. Therefore, the main aim of this paper is to conduct a systematic study to determine the optimum cutting conditions, analysis of vibration and surface roughness under different cutting speeds, feed rates and cutting edge angles using response surface methodology (RSM). Prediction models were developed and optimum turning parameters were obtained for averaged surface roughness (Ra) and three components of vibration (axial, radial and tangential) using RSM. The results demonstrated that the feed rate was the most affecting parameter in increasing the surface roughness (69.4%) and axial vibration (65.8%) while cutting edge angle and cutting speed were dominant on radial vibration (75.5%) and tangential vibration (64.7%), respectively. In order to obtain minimum vibration for all components and surface roughness, the optimum parameters were determined as Vc = 190 m/min, f = 0.06 mm/rev, Κ = 60° with high reliability (composite desirability = 90.5%). A good agreement between predicted and measured values was obtained with the developed model to predict surface roughness and vibration during turning of AISI 5140 within a 10% error range.
Atıf Yapan Makale Bilgileri
Kurumlar (5)
Bydgoszcz University of Science and Technology
Bydgoszcz, Poland
I.K. Gujral Punjab Technical University, Jalandhar
Jalandhar, India
Selçuk Üniversitesi
Selçuklu, Turkey
South Ural State University
Chelyabinsk, Russian Federation
University of Portsmouth
Portsmouth, United Kingdom