2019
DOI: 10.1088/2053-1591/ab1ae0
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Influence of process factors on surface measures on electrical discharge machined stainless steel using TOPSIS

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Cited by 57 publications
(25 citation statements)
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“…The modeling and optimizing technological parameters in PMEDM is preferred as one of the main research direction by many technical experts [32] . Many computational techniques such as Taguchi, ANN, GRA, Topsis, TGRA, etc were successfully applied to optimization in EDM [33][34][35][36][37] . These techniques have also been used to model and optimize single or multiple targets in PMEDM process.…”
Section: Introductionmentioning
confidence: 99%
“…The modeling and optimizing technological parameters in PMEDM is preferred as one of the main research direction by many technical experts [32] . Many computational techniques such as Taguchi, ANN, GRA, Topsis, TGRA, etc were successfully applied to optimization in EDM [33][34][35][36][37] . These techniques have also been used to model and optimize single or multiple targets in PMEDM process.…”
Section: Introductionmentioning
confidence: 99%
“…Multicriteria decision-making to develop surface performance measurement in the EDM process using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has been utilized. Minimum levels of average white layer thickness and surface roughness at maximum compressive residual stress are obtained while machining AISI 304 stainless steel showed the most influent parameter which was current for plasma formation [9]. Taguchi-Grey analysis-based criteria decision-making was applied to evaluate quality characteristics (like recast layer thickness, wire wear ratio, and microhardness) of the wire EDM process.…”
Section: Introductionmentioning
confidence: 99%
“…Sivapirakasam et al, [26] used fuzzy-TOPSIS technique for the optimization of output responses such as process time, relative wear rate of the electrode, process energy and dielectric consumption in EDM process. In the Electrical Discharge Machining of AISI 304 steel, Huo et al, [27] used TOPSIS approach for the multi response optimization and obtained optimal setting for the surface roughness, white layer thickness and compressive residual stress.…”
Section: Introductionmentioning
confidence: 99%