Issue |
Manufacturing Rev.
Volume 2, 2015
|
|
---|---|---|
Article Number | 20 | |
Number of page(s) | 15 | |
DOI | https://doi.org/10.1051/mfreview/2015020 | |
Published online | 26 October 2015 |
Research Article
Modeling and optimization of laser cutting operations
1
Mechanical Design & Production Engineering Department, Faculty of Engineering, Cairo University Egypt, 12316
Cairo, Egypt
2
Production Engineering & Design Department, Faculty of Engineering, Minia University, 61516
Minya, Egypt
* e-mail: mohamed@aucegypt.edu
Received:
4
June
2015
Accepted:
22
August
2015
Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L) considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta), surface roughness (Ra) and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA) are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs) are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.
Key words: Optimization / Laser cutting / Kerf width / Taguchi technique / Response surface methodology / Design of experiments
© M.H. Gadallah and H.M. Abdu, Published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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