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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2018-01-01
|
Series: | MATEC Web of Conferences |
Online Access: | https://doi.org/10.1051/matecconf/201815305005 |
id |
doaj-fddb779ae67f45e2aa293ac7b506cf48 |
---|---|
record_format |
Article |
spelling |
doaj-fddb779ae67f45e2aa293ac7b506cf482021-02-02T09:21:45ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011530500510.1051/matecconf/201815305005matecconf_icmme2018_05005Analysed statistically Modelling and Optimization of Laser Machining by Response Surface MethodologyMizhir HaniJawad KamilH Obaid ZuhairOne 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.https://doi.org/10.1051/matecconf/201815305005 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mizhir Hani Jawad Kamil H Obaid Zuhair |
spellingShingle |
Mizhir Hani Jawad Kamil H Obaid Zuhair Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology MATEC Web of Conferences |
author_facet |
Mizhir Hani Jawad Kamil H Obaid Zuhair |
author_sort |
Mizhir Hani |
title |
Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology |
title_short |
Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology |
title_full |
Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology |
title_fullStr |
Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology |
title_full_unstemmed |
Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology |
title_sort |
analysed statistically modelling and optimization of laser machining by response surface methodology |
publisher |
EDP Sciences |
series |
MATEC Web of Conferences |
issn |
2261-236X |
publishDate |
2018-01-01 |
description |
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. |
url |
https://doi.org/10.1051/matecconf/201815305005 |
work_keys_str_mv |
AT mizhirhani analysedstatisticallymodellingandoptimizationoflasermachiningbyresponsesurfacemethodology AT jawadkamil analysedstatisticallymodellingandoptimizationoflasermachiningbyresponsesurfacemethodology AT hobaidzuhair analysedstatisticallymodellingandoptimizationoflasermachiningbyresponsesurfacemethodology |
_version_ |
1724295245289488384 |