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Application of Grey Theory and Fuzzy Logic to Optimize Machining Parameters of Zircon Sand Reinforced Aluminum Composites
M. Vignesh, , S. Bhattacharya,
Published in Springer
Pages: 653 - 662
The increasing demand for lightweight materials in various engineering and structural applications led to the introduction of aluminum matrix composites (AMC). In this work, a novel zircon sand (ZrSiO4)-reinforced aluminum (grade-LM25) matrix composites were produced using stir casting method, and experimental investigation on machinability based on 18 orthogonal array of mixed level design is carried out formulated by Taguchi. Machining conditions (Dry/MQL), cutting speed (CS), depth of cut (DoC), feed rate (FR) and zircon sand reinforcement are varied in the experiments, and output responses like resultant cutting force (Fr), surface roughness (Ra) and tool wear (TW) were measured. Fuzzy logic (FL), a soft computing technique coupled with one of a multi-objective optimization technique, grey relational analysis (GRA) is implemented to find the optimal cutting parameters. The significant factors are analyzed using ANOVA. The optimum machining levels obtained are MQL cutting environment with a cutting speed of 200 m/min, feed rate of 0.06 mm/rev, depth of cut of 1 mm and 10% zircon sand particle reinforcement. © 2021, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Mechanical Engineering
PublisherData powered by TypesetSpringer