Optimization of Stir-Cast AA6063 Hybrid Composites Reinforced with Rice Husk Ash and Marble Dust Using Taguchi-Grey Relational Analysis

Hybrid aluminium matrix composites (HAMCs) have emerged as promising materials owing to their superior mechanical and tribological performance. In the present study, AA6063-based HAMCs were developed using 5 wt.% silicon carbide (SiC) and 5 wt.% graphite (Gr) as primary reinforcements, along with 1.5–2.5 wt.% rice husk ash (RHA) and marble dust (MD) as secondary reinforcements. The composites were fabricated via stir casting based on a Taguchi L16 orthogonal array, considering pouring temperature (PT) and stirring speed (SS), wt.% RHA and wt.% MD as process parameters. Mechanical and tribological properties, including tensile strength, microhardness, wear rate, and density, were evaluated. Multi-response optimization was carried out using Grey Relational Analysis (GRA), wherein grey relational grades (GRG) were computed and ranked to determine the optimal experimental conditions. Further, analysis of variance (ANOVA) was performed on GRG to identify the significance and contribution of process parameters. The results demonstrate the effectiveness of the integrated Taguchi–GRA approach in determining optimal processing conditions for AA6063 hybrid composites.

Authors

Institutions

Publication Details

Journal
Evergreen
Published
2026-05-16
DOI
https://doi.org/10.5109/7429611
Primary Topic
Aluminum Alloys Composites Properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of Stir-Cast AA6063 Hybrid Composites Reinforced with Rice Husk Ash and Marble Dust Using Taguchi-Grey Relational Analysis

Dheeraj Joshi, Bhavana Mathur, Prashant Kumar
Evergreen
Aluminum Alloys Composites Properties
article

Optimization of Stir-Cast AA6063 Hybrid Composites Reinforced with Rice Husk Ash and Marble Dust Using Taguchi-Grey Relational Analysis

Dheeraj Joshi, Bhavana Mathur, Prashant Kumar
article en

Abstract

Hybrid aluminium matrix composites (HAMCs) have emerged as promising materials owing to their superior mechanical and tribological performance. In the present study, AA6063-based HAMCs were developed using 5 wt.% silicon carbide (SiC) and 5 wt.% graphite (Gr) as primary reinforcements, along with 1.5–2.5 wt.% rice husk ash (RHA) and marble dust (MD) as secondary reinforcements. The composites were fabricated via stir casting based on a Taguchi L16 orthogonal array, considering pouring temperature (PT) and stirring speed (SS), wt.% RHA and wt.% MD as process parameters. Mechanical and tribological properties, including tensile strength, microhardness, wear rate, and density, were evaluated. Multi-response optimization was carried out using Grey Relational Analysis (GRA), wherein grey relational grades (GRG) were computed and ranked to determine the optimal experimental conditions. Further, analysis of variance (ANOVA) was performed on GRG to identify the significance and contribution of process parameters. The results demonstrate the effectiveness of the integrated Taguchi–GRA approach in determining optimal processing conditions for AA6063 hybrid composites.

EvergreenVol. 13(2)
Pathfinder International (US), Institute of Technology Management (IN)
Openalex Percentile: Top 11%
Aluminum Alloys Composites Properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.