Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics

Çaydaş, Ulaş; Hasçalik, Ahmet

doi:10.1016/j.optlastec.2008.01.004

Cited by 197 publications

(56 citation statements)

References 27 publications

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“…This generation is achieved for all the three quality characteristics -smaller-the-better, larger-the-better, and nominal the best. For the current investigation, all the selected quality characteristics are of the type 'larger the better' and grey relational generation is calculated by Equation (1) (Çaydaş & Hasçalık, 2008;Ju-Long, 1982;Kumar, Balaji, & Prrithvi, 2014 (1)…”

Section: Taguchi Approach and Grey Relational Analysismentioning

confidence: 99%

Friction stir welding: multi-response optimisation using Taguchi-based GRA

Kundu

Singh

2016

Production & Manufacturing Research

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In present experimental work, friction stir welding of aluminium alloy 5083-H321 is performed for optimisation of process parameters for maximum tensile strength. Taguchi's L 9 orthogonal array has been used for three parameters -tool rotational speed (TRS), traverse speed (TS), and tool tilt angle (TTA) with three levels. Multi-response optimisation has been carried out through Taguchi-based grey relational analysis. The grey relational grade has been calculated for all three responsesultimate tensile strength, percentage elongation, and micro-hardness. Analysis of variance is the tool used for obtaining grey relational grade to find out the significant process parameters. TRS and TS are the two most significant parameters which influence most of the quality characteristics of friction stir welded joint. Validation of predicted values done through confirmation experiments at optimum setting shows a good agreement with experimental values.

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Section: Taguchi Approach and Grey Relational Analysismentioning

confidence: 99%

Friction stir welding: multi-response optimisation using Taguchi-based GRA

Kundu

Singh

2016

Production & Manufacturing Research

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“…Özellikle 6 mm kalınlığındaki iş parçasının kesilmesinde boyutsal doğruluk üzerinde en etkili parametre olarak lazer gücü tespit edilmiştir (Şekil 3b). St37 çeliğin lazerle kesilmesinde de lazer gücünün kesme hızından daha etkili olduğu tespit edilmiştir [22]. 4 mm kalınlığındaki sac malzemenin anma ölçüsü 28,28 mm olan kare şeklinde kesilmesinde ölçme sonuçları üzerinde bağımsız parametrelerin etkileri Şekil 4a'da verilmiştir.…”

Section: Ana Etki Grafikleri (Main Effect Graphs)unclassified

“…4 mm ve 6 mm AISI 304 malzeme üzerinden kare geometrili profillerin kesiminde, nominal değerden minimum sapma ve ölçüsel tamlık için lazer gücünün optimum değerleri sırasıyla 3400 W ve 3700 W'dir. St37 çeliğin kesilmesinde lazer gücünün kesme ilerlemesi hızından daha etkili olduğu tespit edilmiştir [22]. Bu çalışmada da 6 mm kalınlığındaki parçaların kesilmesinde lazer gücünün ilerleme hızından daha etkili olduğu görülmüştür.…”

Section: Ana Etki Grafikleri (Main Effect Graphs)unclassified

Aisi 304 Çeli̇ği̇ni̇ Farkli Geometri̇lerde Lazerle Kesmede Parametreleri̇n Boyutsal Doğruluk Üzeri̇ne Etki̇leri̇ni̇n Modellenmesi̇

Durukan¹,

Motorcu²,

Güllü³

2014

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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ÖZETBu çalışmada, 4 ve 6 mm kalınlığındaki AISI 304 paslanmaz çelik malzeme üzerinden belirli ölçülerde üçgen, kare ve dairesel şekilli parçalar farklı kesme şartlarında CO 2 lazer kesim tezgâhı ile kesilmiş ve kesilen numunelerin boyutsal doğruluğu üzerinde kesme parametrelerinin etkileri araştırılmıştır. MODELING OF THE EFFECTS OF PARAMETERS ON DIMENSIONAL ACCURACY IN LASER CUTTING OF AISI 304 STEEL WITH DIFFERENT GEOMETRIES ABSTRACTIn this study, some certain sizes of triangular, square and circular shaped parts have been cut through CO 2 laser cutting centre over a 4 and 6 mm thickness of AISI 304 stainless steel material at different cutting conditions and the effects of cutting parameters were investigated on the dimensional accuracy of the samples. As the independent variables, laser power (W), cutting feed rate (F), focus point (ON) and gas pressure (P) have been selected. By using Full Factorial Experimental Design Technique (TFT), a total of 486 experiments have been carried out on the 4 and 6 mm thick sheet materials at three different levels of the independent parameters. Using the experimental data obtained as a result of the measurements made with three-dimensional coordinate measurement machine (CMM), the second-order predictive models, including the effects of laser cutting parameters on the dimensional accuracy of the triangular, square and circular-shaped samples have been improved through the Regression Analysis. Correlation coefficients of the predictive equations developed in the 95% confidence level have been obtained over R 2 =0,78. In this study, furthermore, the main effect graphics showing the effects of independent variables on the dimensional accuracy have also been formed and the effects of parameters were evaluated. The most effective parameters on the dimensional accuracy of the cut parts were laser power, cutting feed rate and focus point, respectively.

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“…The second approach is based on the integration of the Taguchi method (TM) with grey relational analysis, principal component analysis, weighted sum method and fuzzy logic [7,8,11,16,17,18,19,20,21]. The integration of the TM without formulation of any kind of model is an attractive alternative, relatively simple and efficient and became very popular.…”

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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Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics

Cited by 197 publications

References 27 publications

Friction stir welding: multi-response optimisation using Taguchi-based GRA

Friction stir welding: multi-response optimisation using Taguchi-based GRA

Aisi 304 Çeli̇ği̇ni̇ Farkli Geometri̇lerde Lazerle Kesmede Parametreleri̇n Boyutsal Doğruluk Üzeri̇ne Etki̇leri̇ni̇n Modellenmesi̇

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

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