RESPONSE SURFACE METHODOLOGY FOR EFFECTIVE LUBRICATION AND REDUCED TOOL WEAR IN TURNING EN24 STEEL ADALARASAN R. 1* , SANTHANAKUMAR M. 1 1 Department of Mechanical Engineering, Saveetha Engineering College, Chennai, Tamilnadu, India Email: 1 adalarasan@saveetha.ac.in Abstract Turning is an important machining process involving quality characteristics like tool wear and finish of the cut surface. The present work is focused towards the application of response surface methodology (RSM) in turning of EN24 steel. The work observes the effectiveness of the application of minimum quality lubricant (MQL) during the process of turning EN24 steel. The selection of parameters like tool type, work speed, depth of cut and type of lubrication is vital to obtain a good finish and reduced tool wear. Taguchi’s L18 orthogonal array (OA) is used to conduct the turning trials and RSM is applied to predict the optimal turning condition. Key words: EN24 steel; Optimization; response surface methodology; Taguchi; Surface finish. I. INTRODUCTION The EN24 steel finds many applications requiring high strength and wear resistance. The growing industrial application requires a proper study of their machining characteristics. Turning is an important metal removal operation for fabrication of parts in the final stage. However the difficulty in turning EN24 steel has created a good degree of research interest and hence the required drive and motivation. Generally the flank wear of the tool is found to be more at higher cutting speed and feed rate [1]. The effect of various machining parameters can be visualized from the quality characteristics observed in the machined surfaces including tool wear [2-5]. The methods used for solving the multi response problems include the principal component analysis (PCA), grey relational analysis (GRA), technique for order of preference by similarity to ideal solution (TOPSIS), neural networks, genetic algorithm (GA), response surface methodology (RSM) and desirability analysis [6- 10]. Taguchi’s technique employing the concepts of the grey theory is effectively used to identify the grey relational grade. It is used as the performance measure to find the optimal setting of input parameters [11, 12]. Taguchi based method is found to be effective in single response optimization, however a practical situation requires multi response optimization [13, 14]. Taguchi based desirability analysis is observed to predict the optimal variables in different manufacturing operations [15, 16]. The hybrid technique of grey based PCA can be applied to solve problems with a finite number of options. It combines the merits of both the techniques adopted for prediction of optimal variables [17]. The response surface methodology is a numerical technique employed along with the desirability analysis to find the optimal input condition. The technique is used to generate the desirability plots and identify the relation between the variables and observed quality characteristics [18, 19]. From the review of literature, it is observed that optimization of the turning characteristics and a study of lubrication effectiveness is limited in literature, particularly with EN24 steel. Hence the present work is focused towards applying the RSM to identify the optimal turning condition for EN24 steel. II. EXPERIMENTATION AND DESIGN OF TURNING TRIALS The EN24 steel rods of diameter 25 mm are subjected to turning under defined conditions. A center lathe with required accessories and attachments is used for experimentation and a new insert is used during different trials. The input parameters like type of lubrication, tool type, work speed and depth of cut is taken for the study and their levels are found out by pilot trials. The number of input variables and their levels are indicated in Table 1. International Journal on Design & Manufacturing Technologies Vol.10 No.1 January 2016 8