A review of modeling and simulation of laser beam machining

Parandoush, Pedram; Hossain, Altab

doi:10.1016/j.ijmachtools.2014.05.008

Cited by 177 publications

(48 citation statements)

References 81 publications

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“…Nowadays, laser is also finding applications in regenerative machining or rapid prototyping, like stereo-lithography, selective laser sintering etc. The material removal mechanism in LBM process is excellently detailed out ; Parandoush & Hossain, 2014). Dhupal et al (2008) conducted 32 experiments to study the machining characteristics of pulsed Nd: YAG laser during micro-grooving operation on a workpiece of aluminum titanate.…”

Section: Example 3: Laser Beam Machining Processmentioning

confidence: 99%

Parameter selection in non-traditional machining processes using a data mining approach

Dey¹,

Chakraborty²

2015

10.5267/j.dsl

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With ever-increasing demands for high surface finish and complex shape geometries on various difficult-to-machine materials, conventional metal removal methods are now being replaced by nontraditional machining (NTM) processes. These NTM processes use energy in its direct form to remove material from the workpiece surface. They are also cost effective for a wide range of microand nano-level applications. For effective utilization of different NTM processes, it is quite important to study their characteristics and material removal mechanisms in order to identify the most significant control parameters affecting the process responses. In this paper, a data mining approach using classification and regression tree algorithm is employed to identify the most important input parameters of three NTM processes, i.e. micro electro discharge milling process, wire electrical discharge machining process and laser beam machining process. The derived observations are also validated using the analysis of variance results.Growing Science Ltd. All rights reserved. 5

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Section: Example 3: Laser Beam Machining Processmentioning

confidence: 99%

Parameter selection in non-traditional machining processes using a data mining approach

Dey¹,

Chakraborty²

2015

10.5267/j.dsl

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“…Furthermore, the laser beam can heat the material to the evaporation point and the resulting material vapor escapes out of the hole. At this time, steam is formed and released; the waste comes out of the cavity and the molten walls around the cavity are formed (Parandoush et al, 2014, Jay Tu et al, 2014, Dubey et al, 2008 Ghoreishi and Nakhjavani (Ghoreishi et al, 2008) studied an ANN-based process model to find the relation between process parameters (pulse frequency, power, pulse width, number of pulses, assist gas pressure, and focal plane position (FPP)) and output parameters (hole entrance and exit diameters, circularity of hole entrance and hole exit, hole taper) of laser beam percussion drilling (LBPD) using the experimental results. Pulsed Nd:YAG laser source was used to drill the 304 steel sheets with the thickness of 2.5 mm.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Effects of Process Parameters on Laser Percussion Drilling Using Finite Element Methodology; Statistical Modelling and Optimization

Moradi

Golchin

2017

Lat. Am. j. solids struct.

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In the present research, the simulation of the Nickel-base superalloy Inconel 718 fiber-laser drilling process with the thickness of 1mm is investigated through the Finite Element Method. In order to specify the appropriate Gaussian distribution of laser beam, the results of an experimental research on glass laser drilling were simulated using three types of Gaussian distribution. The DFLUX subroutine was used to implement the laser heat sources of the models using the Fortran language. After the appropriate Gaussian distribution was chosen, the model was validated with the experimental results of the Nickel-base superalloy Inconel 718 laser drilling process. The negligible error percentage among the experimental and simulation results demonstrates the high accuracy of this model. The experiments were performed based on the Response Surface Methodology (RSM) as a statistical design of experiment (DOE) approach to investigate the influence of process parameters on the responses, obtaining the mathematical regressions and predicting the new results. Four parameters i.e. laser pulse frequency (150 to 550 Hz), laser power (200 to 500 watts), laser focal plane position (-0.5 to +0.5 mm) and the duty cycle (30 to 70%) were considered to be the input variables in 5 levels and four external parameters i.e. the hole's entrance and exit diameters, hole taper angle and the weight of mass removed from the hole, were observed to be the process output responses of this central composite design. By performing the statistical analysis, the input and output parameters were found to have a direct relation with each other. By an increase in each of the input variables, the entrance and exit hole diameters, the hole taper angel, and the weight of mass removed from the hole increase. Finally, the results of the conducted simulations and statistical analyses having been used, the laser drilling process was optimized by means of the desire ability approach. Good agreement between the simulated and the optimization results revealed that the model would be appropriate for laser drilling process numerical simulation.

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“…These works can be categorized into three different groups. 9 In the first category, the 1D or 2D heat conduction equation was analytically solved to calculate the temperature distribution around the irradiated zone. Hendow and Shakir used an analytical solution of the 2D conduction equation to calculate the temperature distribution and predict the ablation zone.…”

Section: Introductionmentioning

confidence: 99%

3D transient model to predict temperature and ablated areas during laser processing of metallic surfaces

Naghshine

Kiani

2017

AIP Advances

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Laser processing is one of the most popular small-scale patterning methods and has many applications in semiconductor device fabrication and biomedical engineering. Numerical modelling of this process can be used for better understanding of the process, optimization, and predicting the quality of the final product. An accurate 3D model is presented here for short laser pulses that can predict the ablation depth and temperature distribution on any section of the material in a minimal amount of time. In this transient model, variations of thermal properties, plasma shielding, and phase change are considered. Ablation depth was measured using a 3D optical profiler. Calculated depths are in good agreement with measured values on laser treated titanium surfaces. The proposed model can be applied to a wide range of materials and laser systems.

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A review of modeling and simulation of laser beam machining

Cited by 177 publications

References 81 publications

Parameter selection in non-traditional machining processes using a data mining approach

Parameter selection in non-traditional machining processes using a data mining approach

Investigation on the Effects of Process Parameters on Laser Percussion Drilling Using Finite Element Methodology; Statistical Modelling and Optimization

3D transient model to predict temperature and ablated areas during laser processing of metallic surfaces

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