Optimization of laser cutting processes using design of experiments

Huehnlein, K.; Tschirpke, Katrin; Hellmann, Ralf

doi:10.1016/j.phpro.2010.08.050

Cited by 34 publications

(10 citation statements)

References 4 publications

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“…Huehnlein et al [23] employed design of experiments on the cutting of Al 2 O 3 ceramic layers. One factor at a time and interaction effects of decision variables are very time consuming.…”

Section: Introductionmentioning

confidence: 99%

Modeling and optimization of laser cutting operations

Gadallah

Abdu

2015

Manufacturing Rev.

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-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 (T a ), surface roughness (R a ) 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 L 27 OA) 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.

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“…Huehnlein et al [23] employed design of experiments on the cutting of Al 2 O 3 ceramic layers. One factor at a time and interaction effects of decision variables are very time consuming.…”

Section: Introductionmentioning

confidence: 99%

Modeling and optimization of laser cutting operations

Gadallah

Abdu

2015

Manufacturing Rev.

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“…Untuk proses cutting material menggunakan CNC laser cutting, penelitian yang telah dilakukan adalah menggunakan teknik DoE dalam melakukan optimasi [7], selanjutnya penelitian menggunakan DoE untuk menentukan komposisi faktor optimal dalam proses cutting berdasarkan parameter multi respon [8]. Terkait parameter multi respon tersebut beberapa penelitian telah ditujukan untuk material plat logam (metal sheet) [9], logam yang lebih spesifik berjenis stainless steel [10], dan bahkan lebih spesifik lagi berdasarkan ketebalan stainless steel tersebut [11].…”

Section: Tinjauan Pustaka a Mesin Laser Cuttingunclassified

Optimasi Setup Proses Engraving CNC Laser Cutting Material Akrilik Menggunakan Simplex Centroid Design dan Optimasi Respon

Wijaya

Izzhati

2019

DINAREK

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<p>Artikel ini membahas penelitian terkait optimasi komposisi level setup proses engraving mesin CNC laser cutting tipe G-Weike LC6090 terhadap material akrilik. Penelitian ini dibutuhkan karena tidak adanya acuan tabulasi level setup proses engraving pada mesin tersebut, sehingga setup proses hanya berdasarkan perkiraan. Hal ini memunculkan masalah terkait kualitas hasil proses, efisiensi permesinan, dan masa pakai tabung CO2 penghasil laser. Artikel ini memperlihatkan hasil optimasi komposisi level setup optimal proses engraving menggunakan Design of Experiment (DoE) dengan metode Simplex Centroid Design (SCD) dan optimasi multi respon. Faktor komposisi setup dalam penelitian ini adalah kecepatan proses, kekuatan, dan interval pemakanan laser. Sedangkan parameter multi respon yang diukur adalah waktu proses, depth, dan roughness. Model formulasi matematis akan dihasilkan dari setiap parameter responnya, kemudian dilakukan optimasi respon tersebut berdasarkan depth yang diinginkan. Hasil penelitian menunjukkan terdapat trade off dari parameter multi responnya, serta diperoleh komposisi level setup optimal untuk batas depth (p) 0,3 mm ≥ p ≤ 1,34 mm.</p>

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“…Indeed, DoE methods were already successfully tested in studies on laser beam cutting, e.g., Son and Lee [42] investigated CO 2 laser cutting of structural and stainless steel with 2 mm in thickness and applied multiple regression analysis to describe correlations between processing parameters and cutting quality. Huehnlein et al [43] reported on the optimization of laser cutting thin alumina layers based on factor screening and response surface designs. Eltawahni et al [44] applied DoE methods to relate cutting edge quality quantities to process parameters in CO 2 laser cutting of medical grade AISI 316L stainless steel with a thickness of 2 mm.…”

Section: Introductionmentioning

confidence: 99%

Factorial Analysis of Fiber Laser Fusion Cutting of AISI 304 Stainless Steel: Evaluation of Effects on Process Performance, Kerf Geometry and Cut Edge Roughness

2021

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Factorial Design-of-Experiment analyses were applied for conventional and beam oscillation fiber laser cutting of 10 mm thick AISI 304 stainless steel. Considered factors in case of the conventional process with a static beam involve both laser and cutting gas parameters, in particular the laser power, the focal plane position, the cutting gas pressure, the nozzle stand-off distance as well as the nozzle diameter. The conducted trials were evaluated with respect to the achievable cutting speed, the cut kerf geometry and the cut edge roughness. Noticeable correlations between cut edge roughness and cut kerf geometry stimulated the development of a corresponding Computational Fluid Dynamics (CFD) model of the cutting gas flow through the kerf. A specific approach of data synchronization revealed that the experimentally determined roughness values do well correlate with numerically computed values of the backward directed component of the gas-induced shear stress and that the cut kerf geometry as internal process-inherent boundary condition influences relevant cutting characteristics more than controllable external cutting gas parameters. Finally, effects of circular beam oscillation were investigated by an additional factorial analysis considering the laser power, the focal plane position, the oscillation frequency and the oscillation amplitude as factors. The results demonstrate the potential of beam oscillation techniques for quality improvements in laser cutting.

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Optimization of laser cutting processes using design of experiments

Cited by 34 publications

References 4 publications

Modeling and optimization of laser cutting operations

Modeling and optimization of laser cutting operations

Optimasi Setup Proses Engraving CNC Laser Cutting Material Akrilik Menggunakan Simplex Centroid Design dan Optimasi Respon

Factorial Analysis of Fiber Laser Fusion Cutting of AISI 304 Stainless Steel: Evaluation of Effects on Process Performance, Kerf Geometry and Cut Edge Roughness

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