TOPSIS based Taguchi design optimization for CVD growth of graphene using different carbon sources: Graphene thickness, defectiveness and homogeneity

Vertical Graphene Growth on AlCu4Mg Alloy by PECVD Technique

“…It should be noted here that it is the effect of this interaction on the thickness of the vertical graphene when the temperature is fixed at 800 • C, the chamber pressure is 200 mTorr, simultaneously with the methane content at 100%. In other cases, there was no increase in graphene [33,34].…”

“…Unfortunately, at higher values of the Performance parameter, Samples 50 and 54 do not show the same trend as for the above-mentioned samples. From the measured values of the 2D/G ratios it follows that in Samples 16,29,34,45,50,54, and 62 there was deposition according to the definition and thus the growth of several layers of graphene. A 2D/G ratio value of 0.9 to 0.6 corresponds to 3 to 5 layers of planar graphene.…”

Multiple-response optimization of open graded friction course reinforced with fibers through CRITIC-WASPAS based on Taguchi methodology

“…As more than one response is obtained, it is necessary to turn the multiple response into a single response optimization problem. In previous research works, MCDM methods have proved to be an easy and efficient tool to be integrated with the Taguchi method [34,44], being GRA and TOPSIS the most common methodologies for that purpose [46][47][48][49]. This article applies the Weighted Aggregated Sum Product Assessment (WASPAS) methodology to combine all the multi response values of the system into a single response value, thus obtaining the optimum parameter based on the Joint Performance Score (JPS).…”

“…Therefore, it is necessary to turn the multiple responses into a single unique response optimization problem. Previous research works suggested that decision support systems can actually be integrated with the Taguchi technique [34]. As said before, TOPSIS and GRA are the most common techniques to be integrated with Taguchi approach [46][47][48]71].…”

“…independent variables, can be observed in the response or dependent variable. In several fields, DOEs have been extensively applied [31][32][33][34]. For example, Varanda et al [31] adopted a constrained mixture design to optimize a bitumen formulation.…”