Multiple-objective optimization in precision laser cutting of different thermoplastics

Tamrin, Khairul Fikri; Nukman, Y.; Choudhury, Imtiaz Ahmed; Savetlana, Shirley

doi:10.1016/j.optlaseng.2014.11.001

Cited by 57 publications

(38 citation statements)

References 21 publications

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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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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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“…Micromachining using IR (infrared) laser sources particularly using CO 2 laser is common as it allows significantly higher rates of machining [6]. A few studies report the use of CO 2 laser process for polymer waveguide fabrications.…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers have suggested using techniques of soft computing to deal with these complexities [6,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Experiment and Prediction of Ablation Depth in Excimer Laser Micromachining of Optical Polymer Waveguides

Tamrin

Zakariyah

Hossain

et al. 2018

Advances in Materials Science and Engineering

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Extending the data transfer rates through dense interconnections at inter-and intraboard levels is a well-established technique especially in consumer electronics at the expense of more cross talk, electromagnetic interference (EMI), and power dissipation. Optical transmission using optical fibre is practically immune to the aforementioned factors. Among the manufacturing methods, UV laser ablation using an excimer laser has been repeatedly demonstrated as a suitable technique to fabricate multimode polymer waveguides. However, the main challenge is to precisely control and predict the topology of the waveguides without the need for extensive characterisation which is both time consuming and costly. In this paper, the authors present experimental results of investigation to relate the fluence, scanning speed, number of shots, and passes at varying pulse repetition rate with the depth of ablation of an acrylate-based photopolymer. e depth of ablation essentially affects total internal reflection and insertion loss, and these must be kept at minimum for a successful optical interconnection on printed circuit boards. e results are then used to predict depth of ablation for this material by means of adaptive neurofuzzy inference system (ANFIS) modelling. e predicted results, with a correlation of 0.9993, show good agreement with the experimental values. is finding will be useful in better predictions along with resource optimisation and ultimately helps in reducing cost of polymer waveguide fabrication.

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“…Hybrid approach of grey based response surface methodology for predicting the optimal combination of laser cutting parameters is used. A grey relational analysis is used to determine a single optimized set of cutting parameters in precision laser cutting of three different thermoplastics [9]. It is found that the laser power has dominant effect on heat affected zone for all thermoplastics.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Process Parameters for Cut Quality in CO2 Laser Cutting Using Taguchi Method

Begić-Hajdarević¹,

Pasic²,

Čekić³

et al. 2016

Proceedings of the 27th International DAAAM Symposium 2016

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Laser cutting is a popular manufacturing process utilized to cut various types of materials. There are many non-linear interaction factors responsible for the performance of the laser cutting process. Identification of dominant factors that significantly affect cut quality is important. In this paper, the effect of the process parameters is analysed on the laser cut quality of an uncommon alloy, the tungsten alloy sheet with thickness of 1 mm. The experiments are conducted at three levels of the selected process parameters such as assist gas type (oxygen, air and nitrogen) and assist gas pressure. Taguchi design of experiments is used to obtain the optimum conditions through the study of signal to noise ratio for three quality characteristics such as kerf width, heat affected zone and surface roughness. Results of this study indicate that the optimal assist gas pressure is entirely different for kerf width, heat affected zone and surface roughness. The nitrogen as assist gas is suggested as the optimal assist gas for all of three quality characteristics.

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Multiple-objective optimization in precision laser cutting of different thermoplastics

Cited by 57 publications

References 21 publications

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

Experiment and Prediction of Ablation Depth in Excimer Laser Micromachining of Optical Polymer Waveguides

Optimization of Process Parameters for Cut Quality in CO2 Laser Cutting Using Taguchi Method

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