Modelling and optimization of cut quality during pulsed Nd:YAG laser cutting of thin Al-alloy sheet for curved profile

Sharma, Amit; Yadava, Vinod

doi:10.1016/j.optlaseng.2012.07.012

Cited by 52 publications

(21 citation statements)

References 29 publications

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“…The calculated weights of surface roughness, micro-hardness and MRR are found to be 0.333228, 0.332224 and 0.334548, respectively.The estimated weight factor of each output parameters are roughly equivalent. The similar types of results are obtained by several researchers during weight determination in optimization of process parameters in turning, EDM and laser process [14,29,30]. Based on the high value of normalized assessment, a cutting The optimum result of nose radius is 0.4 mm.…”

Section: Resultssupporting

confidence: 63%

“…Better machining characteristics were obtained using this integrated approach. Sharma and Yadava [30] used simultaneous multi-objective optimization using GRA coupled with entropy method. This technique was applied to convert multi-objective optimization into an equivalent single objective optimization.…”

Section: Weight Criteria Calculation Using Entropy Concept In Multi-omentioning

confidence: 99%

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Multi-Objective Optimization of Turning Parameters Using the Combined Moora and Entropy Method

Singaravel

Selvaraj

Vinodh

2016

Transactions of the Canadian Society for Mechanical Engineering

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Selection of optimum machining parameters in machining operations leads to good functional attributes for the machined components and increased productivity. In this work, machining parameters and nose radius are optimized in turning of EN25 steel with coated carbide tool by the application of combined Multi-Objective Optimization by Ratio Analysis (MOORA) and entropy measurement method. The selected machining parameters are cutting speed, feed rate, depth of cut and nose radius for minimization of surface roughness, micro-hardness and maximization of Material Removal Rate (MRR). Entropy concept has been used to assign the weight criteria of each objective being considered. The optimum combination of machining parameters and nose radius are obtained using normalized assessment values. The results obtained in the analysis are validated and the results based on turning process responses can be effectively improved.

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Section: Resultssupporting

confidence: 63%

Section: Weight Criteria Calculation Using Entropy Concept In Multi-omentioning

confidence: 99%

Multi-Objective Optimization of Turning Parameters Using the Combined Moora and Entropy Method

Singaravel

Selvaraj

Vinodh

2016

Transactions of the Canadian Society for Mechanical Engineering

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“…Various researchers had attempted to determine the optimum combination of process parameters for laser cutting process using techniques such as Taguchi method, response surface methodology, gray-relational analysis, neural networks, GA, SA, PSO, and ABC (Yusup et al 2012;Rao and Kalyankar 2014;Thawari et al 2005;Jimin et al 2006;Almeida et al 2006;Nakhjavani and Ghoreishi 2006;Dubey and Yadava 2008;Sivarao et al 2009;Kuar et al 2010;Pandey and Dubey 2012;Kondayya and Krishna 2013;Sharma and Yadava 2013;Mukherjee et al 2013;Tamrin et al 2015). Now, NSTLBO algorithm is applied to solve the multiobjective optimization problem for laser cutting process.…”

Section: Optimization Of Process Parameters Of Laser Cutting Processmentioning

confidence: 99%

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

Rao

2015

Teaching Learning Based Optimization Algorithm

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Multiobjective optimization aspects of a traditional machining process namely surface grinding and five modern machining processes namely, wire-electro discharge machining process, micro-wire-electric discharge machining process, laser cutting process, electrochemical machining process, and electrochemical discharge machining process are presented in this chapter. A posteriori multiobjective optimization algorithm named as nondominated sorting teaching-learning-based optimization (NSTLBO) algorithm is proposed to solve the multiobjective optimization problems of the machining processes. A Pareto optimal set of solutions along with a Pareto front is presented for each of the considered machining processes.

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“…As well known, an increase of laser power normally causes a widening of kerf and heat affected zone (HAZ) throughout the sheet thickness, whereas increasing cutting speed has an opposite effect. Since cut quality and maximization of productivity are also driven by a proper selection of other cutting parameters, studies have also assessed the effects of assist gas and its pressure, standoff distance, pulse frequency and duty cycle of laser source, cutting path, and so forth [6][7][8][9][10][11], sometimes with discordant results.…”

Section: Introductionmentioning

confidence: 99%

“…Accordingly, laser cutting parameters must be set and tuned properly (repeating experimental activities) whenever sheets are made of different steel grades, have different thicknesses and/or coating layers to guarantee the desired cut quality and reliability. In this regard, response surface methodology, Taguchi design of experiments, and statistical analysis are common methods that can be effectively used to evaluate the effects of laser parameters and their interactions on cut quality by employing a limited number of runs, as well as to define analytical models that are devoted to assessing optimal cutting conditions [2,6,7,[11][12][13]. Hybrid computer-integrated systems, which combine experimental knowledge and numerical simulation, could also be employed to select optimal cutting strategies to improve process accuracy and productivity, as for [14].…”

Section: Introductionmentioning

confidence: 99%

CO2 Laser Cutting of Hot Stamping Boron Steel Sheets

Spena

2017

Metals

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This study investigates the quality of CO 2 laser cutting of hot stamping boron steel sheets that are employed in the fabrication of automotive body-in-white. For this purpose, experimental laser cutting tests were conducted on 1.2 mm sheets at varying levels of laser power, cutting speed, and oxygen pressure. The resulting quality of cut edges was evaluated in terms of perpendicularity tolerance, surface irregularity, kerf width, heat affected zone, and dross extension. Experimental tests were based on a L9(3 4 ) orthogonal array design, with the effects of the process parameters on the quality responses being determined by means of a statistical analysis of variance (ANOVA). Quadratic mathematical models were developed to determine the relationships between the cutting parameters and the quality responses. Finally, a routine based on an optimization criterion was employed to predict the optimal setting of cutting factors and its effect on the quality responses. A confirmation experiment was conducted to verify the appropriateness of the optimization routine. The results show that all of the examined process parameters have a key role in determining the cut quality of hot stamping boron steel sheets, with cutting speed and their interactions having the most influencing effects. Particularly, interactions can have an opposite behavior for different levels of the process parameters.

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Modelling and optimization of cut quality during pulsed Nd:YAG laser cutting of thin Al-alloy sheet for curved profile

Cited by 52 publications

References 29 publications

Multi-Objective Optimization of Turning Parameters Using the Combined Moora and Entropy Method

Multi-Objective Optimization of Turning Parameters Using the Combined Moora and Entropy Method

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

CO2 Laser Cutting of Hot Stamping Boron Steel Sheets

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