Experimental investigations and multiple criteria optimization during milling of Graphene Oxide (GO) doped epoxy/CFRP composites using TOPSIS-AHP hybrid module

Kumar, Jogendra; Verma, Rajesh

doi:10.5937/fme2003628k

Cited by 32 publications

(15 citation statements)

References 23 publications

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“…Park et al noted that the cutting edge of the cutting tool was exposed to more abrasive fibers and the cutting tool was exposed to more hole surface friction with an increasing feed rate [35]. The ANOVA was performed to determine the effects of the factors on processing performances [36]. Table 4 presents the ANOVA results for Ft depending on the control factors.…”

Section: Thrust Forcementioning

confidence: 99%

Multi-objective optimization of process parameters for drilling fibermetal laminate using a hybrid GRA-PCA approach

Eki̇ci̇¹,

Motorcu²,

Uzun³

2021

FME Transactions

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This study investigated the effects of drilling parameters and cutting tool coating conditions on the thrust force, surface roughness, and delamination factor in the drilling of fiber-reinforced carbon reinforced aluminum laminate (CARALL) composite, a commercial type of fibermetal laminate. Gray relational analysis (GRA) was used as a multi-objective optimization method to determine optimum processing parameters and principal component analysis (PCA) was used to determine the weights. According to the findings of this experimental study, the most effective control factors for the thrust force, surface roughnes, and delamination factor were the feed rate, tool coating condition-cutting speed interaction, and tool coating condition, with 93.87%, 66.504%, and 29.137% contribution rates, respectively. From the results of the GRA-PCA analysis, the optimum levels of the control factors were determined as 110 m/min cutting speed, 0.1 mm/rev feed rate, and the uncoated tool.

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Section: Thrust Forcementioning

confidence: 99%

Multi-objective optimization of process parameters for drilling fibermetal laminate using a hybrid GRA-PCA approach

Eki̇ci̇¹,

Motorcu²,

Uzun³

2021

FME Transactions

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“…The TOPSIS and Analytic Hierarchy Process (TOPSIS-AHP) hybrid MCDM approach has simpler calculations than the other traditional optimization methods, and reduces computational efforts. Therefore, this optimization method can be applied to different conflicting responses in machining situations [42]. In this study, the hybrid method was used to substitute the GRC into the TOPSIS process to evaluate the distances between the data chain.…”

Section: Grey-topsis Studymentioning

confidence: 99%

Drilling Process on CFRP: Multi-Criteria Decision-Making with Entropy Weight Using Grey-TOPSIS Method

Tran¹,

Nguyen

Huang³

2020

Applied Sciences

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Moisture strongly affects the quality and mechanical specificity of carbon fiber reinforced plastic (CFRP) when using lubrication fluids during machining, and the significant impact of the cutting tool geometry and cryogenic gas cooling on CFRP machining capabilities are observed. The main body of this paper aims at making decisions about the optimum parameter of the drilling process while machining on CFRP base on the grey relational coefficient embed to the technique for order of preference by similarity to an ideal solution (Grey-TOPSIS). The entropy method was used to determine the weight of decision-making for handling a multiple measure decision-making response. The twist angle of the tool drill, lubrication, and feed rate were used as the input variables, and were analyzed while taking into account several multi-response outputs, such as the surface roughness, uncut fiber, and delamination. The result showed that a feed rate of 228 mm/min, the high-helix twist angle, and cryogenic CO2 lubrication leads the calculated value to close the relative value, which minimizes the value of the surface roughness, the uncut fiber, and the delamination. Finally, verification of the valid effect of each parameter process was conducted using analysis of variance. The results indicated that the lubrication was the highest remarkable criterion on the uncut fiber, the delamination, and the surface roughness. By integrating the advantage of grey systems theory, and the technique for order preference by similarity to an ideal solution, to evaluate and optimize the machining parameter, the results indicate that the proposed model is useful to facilitate the multi-criteria decision-making problem under the environment of uncertainty and vagueness. This relatively advanced approach is very effectual in rejecting process variation and a great assistive strategy than other multi-criteria decision-making approaches.

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“…Therefore, the application of the Taguchi method to design the experiments in this case is very suitable. TOPSIS method that is the multi-objective optimization were successfully applied in many studies with different research fields [25][26][27][28][29][30][31]. However, so far, it seems that the application of TOPSIS method to solve the multi-objective optimization in grinding process using segmented grinding wheel have not been performed in any studies.…”

Section: Introductionmentioning

confidence: 99%

Application of TOPSIS Method in Multi-Objective Optimization of the Grinding Process Using Segmented Grinding Wheel

Trung¹,

Thien²,

Nguyen³

2021

Tribol. Ind.

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Using a segmented grinding wheel improves chip release and heat release condition out of the cutting zone, facilitates the introduction of coolant into the cutting zone, as well as increases the ability to clean the grinding wheel surface. Therefore, using segmented grinding wheel promises to improve the quality and efficiency of the machining process. This paper presents a study about the multi-objective optimization of grinding process using a segmented grinding wheel. The parameters that are shosen as the output criteria are the surface roughness, amplitudes of system vibrations in X, Y, Z directions (Ax, Ay, Az), and the material removal rate (MRR). The experiments were performed in the surface grinding machine with the workpiece material of DIN 1.2379 steel and the grinding wheel material of aluminum oxide. The experimental matrix was designed using Taguchi method with nine experiment (orthogonal array L9) and with four input parameters (number of grooves, workpiece velocity, feed rate, and depth of cut). From the experimental data, the influence of input parameters on the output parameters were investigated. The TOPSIS method was applied to solve the multi-objective optimization problem. Then, the optimized set of input parameters was determined to ensure the minimum value of surface roughess, minimum values of three vibarion components, and to ensure the maximum value of MRR. Finally, the future research directions of this study were also proposed.

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Experimental investigations and multiple criteria optimization during milling of Graphene Oxide (GO) doped epoxy/CFRP composites using TOPSIS-AHP hybrid module

Cited by 32 publications

References 23 publications

Multi-objective optimization of process parameters for drilling fibermetal laminate using a hybrid GRA-PCA approach

Multi-objective optimization of process parameters for drilling fibermetal laminate using a hybrid GRA-PCA approach

Drilling Process on CFRP: Multi-Criteria Decision-Making with Entropy Weight Using Grey-TOPSIS Method

Application of TOPSIS Method in Multi-Objective Optimization of the Grinding Process Using Segmented Grinding Wheel

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