Optimization and measurement of flank wear and surface roughness via Taguchi based grey relational analysis

Abstract

ABSTRACT This study examined experimentally and statistically the machinability of AISI 430 stainless steel on a lathe using two type different coated tool inserts, three various cutting speeds (80, 140, 200 m/min) and three various feed rates (0.75, 1.5, 2.25 mm/rev). Experimental studies were carried out using a coolant and cutting depth of 1.5 mm was used constant under all experiment conditions. In the machinability tests, the impact of turning parameters and levels on Ra and the amount of wear on the cutting tool were examined. The impact of machinability parameters on VB and Ra were calculated using analysis of variance, which determined that feed rate was the most powerful machining parameter for the VB and Ra. Taguchi-based gray relational analysis was performed to find out the ideal machining orders for Ra and VB. According GRA, the percentage of improvement in the gray relational degree was calculated as 69.1%. As a result of this work, multiple performance outputs (surface roughness-flank wear) were improved considerably in machining of difficult-to-machine AISI 430 stainless steel.