Surface Roughness Model and Parametric Welding Optimization in Friction Stir Welded AA2017 Using Taguchi Method and Response Surface Methodology

2015 ◽  
pp. 83-93 ◽  
Author(s):  
Khaled Boulahem ◽  
Sahbi Ben Salem ◽  
Jamel Bessrour
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Taguchi Method ◽  
Response Surface ◽  
Friction Stir ◽  
Roughness Model

Surface Roughness Prediction in the End Milling Parameters of Aluminum Nitride Ceramic by Response Surface Methodology

2010 ◽  
Vol 154-155 ◽  
pp. 626-633
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou-El-Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
End Milling ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Roughness Model ◽  
Roughness Prediction ◽  
Grinding Tool

The present experimental study aimed to examine the selected machining parameters on Surface roughness in the machining of alumina nitride ceramic. The influence of cutting speed and feed rate were determined in end milling by using Cubic boron nitride grinding tool. The predictive surface roughness model has been developed by response surface methodology. The response surface contours with respect to input parameters are presented with the help of Design expert software. The adequacy of the model was tested by ANOVA.

Surface Roughness Model for Helical Milling of Die-Steel Based on Response Surface Methodology

2010 ◽  
Vol 431-432 ◽  
pp. 346-350 ◽  
Author(s):  
Xu Da Qin ◽  
Song Hua ◽  
Xiao Lai Ji ◽  
Shi Mao Chen ◽  
Wang Yang Ni
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Axial Direction ◽  
Helical Milling ◽  
Design Parameters ◽  
Die Steel ◽  
Roughness Model ◽  
Milling Operation ◽  
Hole Making

Holes making process is widely applied in die steel machining, Helical milling a hole, also called orbital drill, is hole making process by milling in which the center of end mill orbits around the center of the hole while spinning on its axis and moving in the axial direction. The paper presents the secondary regression prediction model of the holes surface roughness for helical milling of die-steel. To minimize the number of experiments for the design parameters, response surface methodology (RSM) with orthogonal rotatable central composite design is used. By means of variance analyses and additional cutting experiments, the adequacy of this model is confirmed. The model will be helpful in selecting cutting conditions to meet surface finish requirements in helical milling operation.

Surface Roughness Prediction Model in Machining of 34CrMo4 Steel with Several Tools Using Response Surface Methodology

2012 ◽  
Vol 445 ◽  
pp. 90-95
Author(s):  
Hamed Barghikar ◽  
Amin Poursafar ◽  
Abbas Amrollahi
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Mean Values ◽  
Roughness Model ◽  
34Crmo4 Steel

The surface roughness model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radius under different cutting conditions. The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels.The established equation and graphs show that the feed rate and cutting speed were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut, but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant. However, it could be seen that the first-order affect of feed rate was significant while cutting speed and depth of cut was insignificant.The predicted surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

scholarly journals Optimization of the Surface Roughness Parameters of Ti–Al Intermetallic Based Composite Machined by Wire Electrical Discharge Machining

Coatings ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 900 ◽  
Author(s):  
Sonia Ezeddini ◽  
Mohamed Boujelbene ◽  
Emin Bayraktar ◽  
Sahbi Ben Salem
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Taguchi Method ◽  
Response Surface ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Roughness Parameters ◽  
Surface Roughness Parameters

This work presents a comprehensive research using the Taguchi method and response surface methodology (RSM) to predict surface roughness parameters in wire electrical discharge machining (WEDM) manufacturing for a novel Ti–Al intermetallic based composite that was developed at Supmeca, a composite design laboratory for aeronautical applications in Paris, France. At the first stage, a detailed microstructure analysis was carried out on this composite. After that, the cutting parameters of the WEDM process were determined: Start-up voltage U, Pulse-on-time Ton, speed advance S and flushing pressure p were selected to find out their effects on surface roughness Ra. In the second stage, analyses of variance (ANOVA) were used as the statistical method to define the significance of the machining parameters. After that, an integrated method combining the Taguchi method and the response surface methodology (RSM) was used to develop a predictive model of the finish surface. The microstructure of the surface and subsurface of the cut edge, the micro-cracks, debris and craters and surface roughness of the specimens cut at the altered conditions were evaluated by scanning electron microscopy (SEM) and 3D-Surfscan.

Using Taguchi method & response surface methodology for examination of surface roughness

2018 ◽  
Vol 87 (1) ◽  
pp. 42-54
Author(s):  
Yallamati Abshalomu ◽  
Vinjavarapu Sanakararao ◽  
Ashok Nanduri
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Taguchi Method ◽  
Response Surface

Multi-Objective Optimization of Surface Roughness and Cutting Forces in Hard Milling Using Taguchi and Response Surface Methodology

2018 ◽  
Vol 773 ◽  
pp. 220-224 ◽  
Author(s):  
Ngoc Chien Vu ◽  
Shyh Chour Huang ◽  
Huu That Nguyen
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Taguchi Method ◽  
Response Surface ◽  
Cutting Forces ◽  
Machining Process ◽  
Process Conditions ◽  
Multi Objective Optimization ◽  
Hard Milling ◽  
Multi Objective

Cutting forces and surface roughness are important output parameters affecting the machining performance and quality of any machined surface in hard milling. In order to obtain the best surface quality and highest productivity, the input-cutting parameters need be considered and chosen properly whenever hard milling is involved. Therefore, in this paper, an attempt is made to conduct the multi-objective optimization of the surface roughness (Ra) and the resultant cutting force (Ft) in hard milling of SKD61 steel by Taguchi method and Response Surface Methodology (RSM). Values of the input parameters for milling tests are chosen through the stability lobe diagram of a machine tool simulated by the use of Cutpro software. The Taguchi method is used for designing all of the milling experiments. The values of Ra and Ft are measured by a Surftest SJ-400 and a dynamometer, respectively, and then analysis of variance is conducted to find out the effect of machining process conditions on Ra and Ft. In order to get the low Ft and Ra, a multi-objective optimization is implemented with the use of the desirability function. The results reveal that the optimized machining conditions for Ra and Ft are a cutting speed of 100 m/min, a feed rate of 0.015 mm/tooth, and a depth of cut of 0.44 mm, with predicted Ra of 0.206 µm and Ft of 66.58 N.

Sign in / Sign up

Export Citation Format

Share Document