Welding parameters optimization in MMAW assisted nano-structured hardfacing using desirability function analysis embedded with taguchi method

Abstract

In the assembling enterprises, welding assisted hardfacing has pulled in expanding consideration for its powerful protection against erosion, thermal shock, and abrasion. Nano-particle reinforcements can fundamentally enhance the mechanical properties of the lattice by more viably advancing the molecule solidifying components than micron estimate particles. This paper presents the multitarget optimization of manual metal arc welding (MMAW) process parameters in hardfacing with Nano-technology based electrode. Experimentation was arranged according to Taguchi’s orthogonal array. In this paper, tests have been led utilizing welding current, arc voltage, welding speed as input process parameters for assessing numerous responses in particular weld bead width, reinforcement and bead hardness. A mix of Taguchi’s robust design idea with desirability function analysis (DFA) has been connected to enhance the process parameters. A composite desirability value is gotten for the multi-responses utilizing individual desirability values from the DFA. In light of composite desirability value, the best possible levels of parameters have been distinguished.