Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology

One of the important goals of this research is to predict a relationship between the process input parameters and resultants from surface roughness features through developing a laser cutting model. In most engineering applications, natural sciences and computing; statistical methods, which are one...

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Bibliographic Details
Main Authors: Mizhir Hani, Jawad Kamil, H Obaid Zuhair
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201815305005
Description
Summary:One of the important goals of this research is to predict a relationship between the process input parameters and resultants from surface roughness features through developing a laser cutting model. In most engineering applications, natural sciences and computing; statistical methods, which are one of mathematical branch are widely used for investigating the results. Laser cutting process of stainless steel (2205) is a machining process selected for this study. The technique which adopted here is a response surface methodology (RSM). The main portion for this study is the influence of cutting speed on surface quality. To study the model response, and for statistical approach with further prediction; a mathematical based model has been developed through regression analysis. It’s found that as one of the important results in this research, that cutting speed and surface roughness has a significant rule on the model response. To produce a good surface roughness, it’s approved that the high cutting speed connected with high power regardless of high pressure has a high influence on surface quality.
ISSN:2261-236X