A grey-fuzzy based multi-response optimisation study on the friction and wear characteristics of titanium diboride reinforced aluminium matrix composite

Abstract

Aluminium matrix composites are nowadays used globally as a substitute for other cast alloys because of their augmented properties. The present experiment deals with the fabrication and characterisation of tribological behaviour of titanium diboride reinforced aluminium matrix composite on a pin-on-disc tribotester under dry sliding condition. In this work, an attempt has been made to minimise the friction and wear characteristics of Al2024-TiB2 composite, by optimising the tribological parameters viz. applied load, sliding speed and sliding distance using grey-fuzzy approach. The tests are carried out based on Taguchi’s L25 orthogonal array. Grey-fuzzy analysis is used for converting the multi-objective optimisation problem into a single-objective optimisation. Based on the grey-fuzzy analysis, the optimal combination of tribological parameters is L1S4D2 (10N load, 2.0 m/s sliding speed and 1000 m sliding distance). The optimal combination of parameters has also been validated with a confirmatory experiment. Analysis of variance (ANOVA) for grey fuzzy grade shows that sliding distance is the most significant parameter affecting tribological performance. SEM analysis of the worn surfaces revealed that, increase in sliding distance results in wear transition from mild to severe. The proposed grey-fuzzy method is found to be successful in solving multi-response tribological problems.

Multi-Weld Quality Optimization of Gas Tungsten Arc Welding for Aluminium 6061 using the Grey Relation Analysis-Based Taguchi Method

“…The outcomes are improved when AA 4043 is utilized rather than AA 4047. The weld zone's front breadth and height, which dictates its geometry, determine the superiority of a TIG weld [14][15][16].…”

“…Based on the obtained results, it can be extrapolated that the Grey-Taguchi approach is a valuable tool in improving the tribological performance of Al2024-TiB2 composites. Dipankar Dey et al, [15] The multi-objective optimization problem is transformed into a single-objective optimization by applying grey-fuzzy analysis. Based on the grey-fuzzy analysis, the optimal combination of tribological parameters is L1S4D2, which corresponds to a load of 10N, a sliding speed of 2.0 m/s, and a sliding distance of 1000 m. An additional confirmatory experiment has been employed to authenticate the optimal set of parameters.…”