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dc.contributor.authorAntil, Parvesh-
dc.contributor.authorSingh, Sarbjit-
dc.contributor.authorKumar, Sundeep-
dc.contributor.authorManna, Alakesh-
dc.contributor.authorKatal, Nitish-
dc.identifier.issn0975-1017 (Online); 0971-4588 (Print)-
dc.description.abstractThe acceptance of electrically nonconductive fibrous materials has been increased over the past decade in industrial applications due to their better strength to weight ratio and electrically nonconductive nature. But precise machining of these types of materials has always been a challenging task for the research fraternity. The precise machining of these materials refers to reduced overcut along with significant material removal rate (MRR). In such perspective, multi-objective genetic algorithm (MOGA) evident to be suitable optimization technique for prediction and process selection in manufacturing industries. The present paper deals with multi-objective optimization of electrochemical discharge machining (ECDM) process parameters during machining of SiCp and glass fibers reinforced polymer matrix composites (PMCs) using MOGA. The experiments have been designed as per Taguchi’s design of experiments using L16 orthogonal array. Electrolyte concentration, inter-electrode gap, duty factor, and voltage have been used as process parameters whereas MRR and overcut have been observed as output quality characteristics (OQCs). The obtained experimental results have been optimized by multi-response optimization technique MOGA to attain high MRR with minimum possible overcut. The quality of machined holes has been analyzed using scanning electron microscope (SEM). The analysis reveals that result optimized through MOGA produces enhanced output quality characteristics.en_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJEMS Vol.26(3&4) [June & August 2019]en_US
dc.subjectElectrochemical discharge machiningen_US
dc.subjectLevel diagramsen_US
dc.subjectMulti-objective genetic algorithm (MOGA)en_US
dc.subjectPareto optimal seten_US
dc.subjectPolymer matrix compositesen_US
dc.subjectTaguchi’s methodologyen_US
dc.titleTaguchi and multi-objective genetic algorithm-based optimization during ECDM of SiCp/glass fibers reinforced PMCsen_US
Appears in Collections:IJEMS Vol.26(3&4) [June & August 2019]

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