Title : ( A Statistical Approach for Predicting andOptimizing Depth of Cut in AWJ Machiningfor 6063-T6 Al Alloy )
Authors: Farhad Kolahan , abdolhamid khajavi ,
Full TextAbstract
In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.
Keywords
, AWJ machining, Mathematical modeling, Simulated Annealing, Optimization
@article{paperid:1015469,
author = {Kolahan, Farhad and Khajavi, Abdolhamid},
title = {A Statistical Approach for Predicting andOptimizing Depth of Cut in AWJ Machiningfor 6063-T6 Al Alloy},
journal = {International Journal of Mechanical Systems Science and Engineering },
year = {2010},
volume = {2},
number = {2},
month = {February},
issn = {1307-7473},
pages = {143--146},
numpages = {3},
keywords = {AWJ machining; Mathematical modeling; Simulated Annealing; Optimization},
}
%0 Journal Article
%T A Statistical Approach for Predicting andOptimizing Depth of Cut in AWJ Machiningfor 6063-T6 Al Alloy
%A Kolahan, Farhad
%A Khajavi, Abdolhamid
%J International Journal of Mechanical Systems Science and Engineering
%@ 1307-7473
%D 2010
