scholarly journals Optimization of Carburized UNS G10170 Steel Process Parameters Using Taguchi Approach and Response Surface Model (RSM)

2014 ◽  
Vol 02 (06) ◽  
pp. 566-578 ◽  
Author(s):  
Olawale Samuel Fatoba ◽  
Olaitan Lukman Akanji ◽  
Abiodun Samson Aasa
Keyword(s):  
Response Surface ◽  
Process Parameters ◽  
Response Surface Model ◽  
Surface Model ◽  
Taguchi Approach

Application of Response Surface Methodology to Predict Ovality of AA6082 Flow Formed Tubes

2013 ◽  
Vol 3 (1) ◽  
pp. 52-65 ◽  
Author(s):  
M. Srinivasulu ◽  
M. Komaraiah ◽  
C.S. Krishna Prasada Rao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Response Surface Model ◽  
Surface Model ◽  
Flow Forming ◽  
Box Behnken Design ◽  
Standard Response ◽  
Tubular Components ◽  
Roller Radius

Flow-forming is eco-friendly, chipless manufacturing process employed in the manufacture of thin walled seamless tubes. Ovality, the out of roundness is one of basic form of errors encountered in the tubular components. In the present research, a response surface model has been developed to predict ovality of AA6082 alloy pre-forms using Design of Experiments. The experiments are performed on a flow forming machine with a single roller. The process parameters selected for the present investigation are axial feed of the roller, the speed of the mandrel, and roller radius. Box-Behnken Design, a standard response surface methodology has been used to conduct the experimental runs. The developed response surface model successfully predicts the ovality of AA6082 flow formed tube within the range of selected process parameters. It has been found that, roller feed is the most important process parameter influencing the ovality of AA6082 flow formed tube.

scholarly journals Effect of input variables uncertainty in free tube hydroforming process

2021 ◽  
Author(s):  
Ali Khalfallah ◽  
Pedro André Prates ◽  
José Valdemar Fernandes
Keyword(s):  
Strain Hardening ◽  
Response Surface ◽  
Process Parameters ◽  
Tube Hydroforming ◽  
Response Surface Model ◽  
Bursting Pressure ◽  
Strain Hardening Exponent ◽  
Surface Model ◽  
Significant Variable ◽  
Hydroforming Process

Tube hydroforming (THF) is a plastic forming process that uses tubes with an initial circular cross section, in which pressurized fluid and axial feeds are applied for producing parts with various cross-sectional shapes. Despite of the complexity of THF process, a great progress in the automotive and aerospace industry has been made due to its advantages, such as, consolidation and weight reduction over conventional stamped and welded parts. The analysis of THF process is typically based on deterministic approaches, excluding scattering effects that influence the process reliability. Thus, robust design of tube hydroforming aims to vanish noise factors effects on process responses by considering the influence of process parameters variability. If this fluctuation is not monitored, then the fluctuation of the hydroformed parts quality may contribute to high scrap rates. In this work, the influence of variability in the THF material and process parameters (e.g. yield stress, strength coefficient, strain hardening exponent, plastic anisotropy, initial tube thickness and bulged length) on the bursting pressure is analyzed resorting to a response surface model. The statistically significant variables, which mostly influence the free bulge hydroforming process, are identified through an analysis of variance. Assuming that the input parameters variability follows the normal distribution, the probability distribution of the bursting pressure is evaluated by involving random process variables into the built response surface model. It was shown that the initial tube thickness is the most statistically significant variable, whereas the strain hardening exponent is the least statistically significant variable.

scholarly journals Fractal Dimension Characterization of Joint Surface Morphology on Dissimilar Friction Stir Lap Welding of Al/Mg

Materials ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 3941 ◽  
Author(s):  
Yadong Zhao ◽  
Yalong Luo ◽  
Zhipeng Zhang ◽  
Haixiao Zhang ◽  
Xuefeng Guo ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Response Surface ◽  
Process Parameters ◽  
Welding Process ◽  
Response Surface Model ◽  
Joint Surface ◽  
Surface Model ◽  
Friction Stir Lap Welding ◽  
Friction Stir ◽  
Lap Welding

The joint surface of the 1060 aluminum and AZ31 magnesium alloy was prepared through friction stir lap welding (FSLW) under different welding process parameters. The joint surface was characterized three-dimensionally using a three-dimensional (3D) optical profiler, and the coordinate data were obtained. The fractal dimension of the joint surface was calculated by the box-width transformation method using a MATLAB program. Furthermore, the influence of the welding process parameters on the fractal dimension of the joint surface was studied. The response surface model was established based on the principle of central composite design (CCD), and analysis of variance (ANOVA) was carried out to test the accuracy of the response surface. The results showed that the joint surface morphology had fractal characteristics, and the fractal dimension could be used as an index to characterize the quality of the joint surface. The change of the welding process parameters had a great impact on the fractal dimension of the joint surface, the interaction between the parameters was small, and the fitting accuracy of the response surface model was high. The fractal dimension of the joint surface decreased with the increase in the welding and rotational speeds and the effect of the rotational speed was more significant.

Sign in / Sign up

Export Citation Format

Share Document