Optimization of surface integrity in face milling of AISI 52,100 alloy steel using Taguchi based grey relational analysis

Abstract

The challenging demand to achieve high quality of the manufactured components, has resulted in development of precision machining processes, which serve as a good alternative to the grinding process. However, high-temperature generation is the major problem in the cutting areas during the machining of difficult-to-cut material; this temperature affects the surface integrity. Therefore, lubrication is required for the removal of heat due to temperature rise at the cutting zone. Because of the adverse effect of flood cooling on the worker's health and the environment, MQL is a suitable substitute to flood cooling. In this study, the effect of process parameters such as cutting speed, feed rate, Depth of cut, lubricant concentration, and flow rate on surface roughness and microhardness was studied during the face milling of AISI 52,100 alloy steel using MQL. Taguchi-based L-27 orthogonal array was used, and multi-response optimization was done using grey relational analysis (GRA). The Depth of cut was the highly influencing factor followed by feed rate, cutting speed, flow rate, and lubricant concentration. The optimum process parameters for the optimized condition for surface roughness and microhardness were cutting speed 150 m/min, feed rate 0.1 mm/rev, Depth of cut 0.3 mm, lubricant concentration 60%, and flow rate 100 ml/hr.