Optimization of machining parameters in turning of Al-SiC-Gr hybrid metal matrix composites using grey-fuzzy algorithm

Metal matrix composites reinforced with graphite particles provide better machinability and tribological properties. The present study attempts to find the optimal level of machining parameters for multi-performance characteristics in turning of Al-SiC-Gr hybrid composites using grey-fuzzy algorithm...

Full description

Saved in:
Bibliographic Details
Published in:Transactions of Nonferrous Metals Society of China Vol. 24; no. 9; pp. 2805 - 2814
Main Authors: SURESH, P., MARIMUTHU, K., RANGANATHAN, S., RAJMOHAN, T.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.09.2014
Subjects:
Algorithms
Aluminum
grey-fuzzy algorithm
hybrid composite
Hybrid composites
Machinability
Metal matrix composites
Optimization
Particulate composites
Turning
grey-fuzzy algorithm
hybrid composite
optimization
turning
ISSN:1003-6326
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Metal matrix composites reinforced with graphite particles provide better machinability and tribological properties. The present study attempts to find the optimal level of machining parameters for multi-performance characteristics in turning of Al-SiC-Gr hybrid composites using grey-fuzzy algorithm. The hybrid composites with 5%, 7.5% and 10% combined equal mass fraction of SiC-Gr particles were used for the study and their corresponding tensile strength values are 170, 210, 204 MPa respectively. Al-10%(SiC-Gr) hybrid composite provides better machinability when compared with composites with 5% and 7.5% of SiC-Gr. Grey-fuzzy logic approach offers improved grey-fuzzy reasoning grade and has less uncertainties in the output when compared with grey relational technique. The confirmatory test reveals an increase in grey-fuzzy reasoning grade from 0.619 to 0.891, which substantiates the improvement in multi-performance characteristics at the optimal level of process parameters setting.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1003-6326
DOI:10.1016/S1003-6326(14)63412-9