Laser beam machining—A review

Dubey, Avanish Kumar; Yadava, Vinod

doi:10.1016/j.ijmachtools.2007.10.017

Cited by 733 publications

(275 citation statements)

References 145 publications

(169 reference statements)

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“…High peak power is capable to cut thicker materials for different applications [5]. Due to shorter wavelength of Nd:YAG laser, it is reflected to a lesser extent by metallic surfaces and high absorptivity of Nd:YAG laser cutting highly reflective materials with relatively less power [6]. Therefore, Nd:YAG laser is suitable for processing of metals in general and reflective materials in particular.…”

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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Section: Introductionmentioning

confidence: 99%

Modeling and optimization of laser cutting operations

Gadallah

Abdu

2015

Manufacturing Rev.

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“…When a high energy density laser beam is focused on work surface the thermal energy is absorbed which heats and transforms the work volume into a molten, vaporized or chemically changed state that can easily be removed by flow of high pressure assist gas jet [3]. LBM has wide range of applications in industries for cutting operation, drilling operation, welding, marking, sintering, heat treating etc.…”

Section: Introduction Laser (Light Amplification For Stimulated Emmentioning

confidence: 99%

Heat Affecting Zone Analysis of Polycarbonate in Laser Beam Machining Using Response Surface Methodology

2016

Arimpie - 2016

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Laser beam machining (LBM) is today the most common industrial application of Laser for almost whole range of engineering materials. The change in metallurgical characteristics of laser machined work parts is mainly governed by Heat Affected Zone (HAZ). Therefore, it is required to minimize the HAZ during laser machining by controlling various factors.In this research paper, the effect of process parameters such as laser power, cutting speed and gas pressure on HAZ for Polycarbonate (PC) material in laser cutting are discussed. L-27 orthogonal array was selected for full factorial design to better understanding of interaction between process parameters. Model equations of HAZ have been selected from literature survey and the values of heat affected zone (HAZ) for Polycarbonate was calculated using these model equations. These model equations provide most affecting parameters, interaction affect of parameters and provide optimized input parameters at optimum HAZ. Entire analysis and optimization process has been done with Minitab® 14 software using Response Surface Methodology (RSM).

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“…Numerous additional advantages such as convenience of operation, high precision, small heat-affected zone (HAZ), minimum deformity, low level of noise, flexibility, ease of automation etc., made laser cutting to become an area of intense research and development activity in the past decade constantly attracting the attention of many researchers and practitioners. Comprehensive review papers summarizing experimental and theoretical studies, developments and opportunities for future research in laser cutting are available in the reference books [3,4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of cut quality characteristic in CO2 laser cutting stainless steel

et al. 2015

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Original scientific paper In this paper, multi-objective optimization of the cut quality characteristics in CO2 laser cutting of AISI 304 stainless steel was discussed. Three mathematical models for the prediction of cut quality characteristics such as surface roughness, kerf width and heat affected zone were developed using the artificial neural networks (ANNs). The laser cutting experiment was planned and conducted according to the Taguchi's L27 orthogonal array and the experimental data were used to train single hidden layer ANNs using the Levenberg-Marquardt algorithm. The ANN mathematical models were developed considering laser power, cutting speed, assist gas pressure, and focus position as the input parameters. Multi-objective optimization problem was formulated using the weighting sum method in which the weighting factors that are used to combine cut quality characteristics into the single objective function were determined using the analytic hierarchy process method. Keywords: analytic hierarchy process; artificial neural networks; CO2 laser cutting; cut quality characteristics; genetic algorithm; multi-objective optimization Višekriterijska optimizacija karakteristika kvalitete reza kod CO2 laserskog rezanja nehrđajućeg čelikaIzvorni znanstveni članak U ovom je radu predstavljena metodologija višekriterijske optimizacije karakteristika kvalitete reza kod CO2 laserskog rezanja AISI 304 nehrđajućeg čelika (korozijski postojanog čelika). Za predviđanje karakteristika kvalitete reza kao što su hrapavost površine reza, širina reza i zona utjecaja topline, kreirani su matematički modeli pomoću umjetnih neuronskih mreža. Eksperiment laserskog rezanja je planiran i izveden prema Taguchijevom L27 ortogonalnom nizu, a eksperimentalni podaci su korišteni za treniranje umjetnih neuronskih mreža pomoću Levenberg-Marquardtovog algoritma. Matematički modeli umjetnih neuronskih mreža su kreirani uzimajući u obzir snagu lasera, brzinu rezanja, tlak pomoćnog plina i položaj fokusa kao ulazne parametre. Problem

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Laser beam machining—A review

Cited by 733 publications

References 145 publications

Modeling and optimization of laser cutting operations

Modeling and optimization of laser cutting operations

Heat Affecting Zone Analysis of Polycarbonate in Laser Beam Machining Using Response Surface Methodology

Multi-objective optimization of cut quality characteristic in CO2 laser cutting stainless steel

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