Optimization of Drilling Process on Al-SiC Composite using Grey Relation Analysis

This study reveals the multi objective optimization of machining parameters in drilling of SiC reinforced with aluminium metal matrix composites through grey relational analysis. The composite is prepared with varying volume fraction of the reinforcement by liquid metal stir casting technique. Unifo...

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Bibliographic Details
Published in:International journal of manufacturing, materials, and mechanical engineering materials, and mechanical engineering, 2015-10, Vol.5 (4), p.17-31
Main Authors: Babu, K Vinoth, Uthayakumar, M, Jappes, J T. Winowlin, Rajan, T P. D
Format: Article
Language:English
Subjects:
Aluminum
Aluminum matrix composites
Analysis of variance
Carbide tools
Costs (Law)
Cutting parameters
Cutting speed
Drilling
Drilling and boring
Founding
Liquid metals
Machining
Mechanical properties
Optimization
Particulate composites
Process parameters
Silicon carbide
Surface roughness
Thrust
Variance analysis
Volume fraction
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Summary:This study reveals the multi objective optimization of machining parameters in drilling of SiC reinforced with aluminium metal matrix composites through grey relational analysis. The composite is prepared with varying volume fraction of the reinforcement by liquid metal stir casting technique. Uniform distribution of SiC particle in the matrix is witnessed through microscopy study and observed that the hardness and strength on different composite. The drilling experiments were performed with coated carbide tool with different point angle such as 90o, 120o and 140o. Cutting speed, feed, point angle and volume fraction are considered as input parameters and the performance characteristics such as surface roughness and thrust force are observed as output response in this study. The significant contributions of these factors are determined using Analysis of Variance (ANOVA). The optimized process parameters have been validated by the confirmation test. The experimental result shows that point angle influences more on output performance followed by feed and cutting speed.
ISSN:2156-1680
2156-1672
DOI:10.4018/IJMMME.2015100102