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publication name Modeling and Optimization of CO2 Laser Turning Process for Armored Steel Assisted by Oxygen
Authors Wisam.M.Farouk, Ahmed.M.Rezk, Wagih.W.Marzouk, Fayz.E.Abo Ghriba, El-Awady.A.Attia
year 2022
keywords Armored steel, Material removal rate (MRR), Response surface methodology (RSM), laser turning process (LTP).
journal ngineering Research Journal
volume 45
issue 2022
pages 341-361
publisher Faculty of Engineering Menoufia University
Local/International Local
Paper Link https://doi.org/10.21608/erjm.2022.131890.1161
Full paper download
Supplementary materials Not Available
Abstract

The current paper investigates the performance of armored steel (500HB) when machined by CO2 laser turning process (LTP) with oxygen gas assistance for grooving operation. The different working parameters were investigated which include; laser power (P), gas pressure (GP) feed rate (F) and motor speed (S). The different groove dimensions and were considered as the model responses which include; depth of cut (DC), upper cut width (UC) and lower cut width (LC), in addition to the performance aspects of root round error and metal removal rate (MRR). For this purpose, a test rig was designed and fabricated. The experimental results are mathematically modeled by response surface methodology. The results are modeled and illustrated to closely understand the effect and surface quality of CO2-LTMP. The optimum process conditions for grooving Armored Steel (500HB) were identified. Results showed that, DC and width of cut and roundness error increase with increasing P and GP, but MRR decreases with increasing F. The motor speed has a moderate effect on the machining process of armored steel under investigation. The optimal combination of machining conditions maximized MRR, DC, LC, UC and minimized root round error to 0.0384 gm, 0.6632 mm, 0.2583 mm, 0.4684 mm and 15.7832 μm respectively. The error between optimum experimental results and the optimum predicted values for MRR, DC, LC, UC and root round error lie within 2.8%, 2.6%, 2.9%, 1% and 6.9%, respectively.

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