Optimization of Stir-Cast AA6063 Hybrid Composites Reinforced with Rice Husk Ash and Marble Dust Using Taguchi-Grey Relational Analysis
1Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur 302017, India
2Department of Mechanical Engineering, Anand International College of Engineering, Jaipur 302012, India
*Author to whom correspondence should be addressed:
E-mail: kprashant709@gmail.com (PK)
E-mail: kprashant709@gmail.com (PK)
Received: April 28, 2025 | Revised: April 04, 2026 | Accepted: April 19, 2026 | Published: June 2026
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.
Keywords
ANOVA; Density; Grey relational analysis; Microhardness; Porosity; Stir casting; Tensile Strength; Wear rate
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