Abstract

Multi-Objective Optimization of Tribological Parameters of Hybrid Composites Using Grey Relational Analysis

Author(s): S. Perumal and J. Udaya Prakash

This paper presents an effective approach for the optimization of the tribological properties of hybrid aluminium matrix composites (356-B4Cp-MoS2) fabricated by stir casting technique, with multiple performance characteristics based on the grey relational analysis. In this study B4C was kept constant at
6% for all three composites (356-6% B4C, 356-6% B4C-2% MoS2 and 356-6% B4C-4% MoS2) and MoS2 was varied from 0 to 4% with an increment of 2 wt%. Dry sliding wear tests were conducted using a standard pin on disc test setup following a well-planned experimental schedule based on Taguchi’s
orthogonal arrays. The input parameters such as sliding speed, sliding distance, load and reinforcement percentages are optimized with considerations of multiple performance characteristics: wear rate, specific wear rate and coefficient of friction. The optimal levels of input parameters were selected from response table and response graph from the grey relational grade. ANOVA was used to find the significance of the
wear parameters.