Optimization of Machining Parameters During Turning of Bearing Steel Using Taguchi -Gra Technique

In present investigation turning of bearing steel performed using coated cutting insert under dry, flood and minimum quantity lubrication (MQL) machining environments. The input variables such as cutting speed, feed rate and depth of cut were selected along with output variables like surface roughness, cutting zone temperature and tool nose radius for optimization. The mono and multi objective optimization performed by utilizing Taguchi and Grey Relational Analysis technique respectively. Both the type of performed optimization showed that under MQL cooling environment better outcomes are achieved as compared to other environments.