PREDICTION AND OPTIMIZATION OF SURFACE ROUGHNESS BY COUPLED STATISTICAL AND DESIRABILITY ANALYSIS IN DRILLING OF MILD STEEL

Surface roughness is a very important parameter for determining the quality of any material which has undergone some machining processes. Now a day in different process and assembly industries the quality measure of the products or required equipments has to satisfy certain level in order to ensure good quality. Also in modern competitive market the cost per unit product is one crucial point which in many cases determines the survivability of the industry. Again quality of the product is something which must be integrated in the product in line with the reduction of cost. Now that's why it is very much important to identify the dominating process parameters which, if can be optimized; the best product with minimum manufacturing cost can be achieved. With this goal, the authors of this paper investigated the effect of different process parameters for a vertical CNC drilling machine in order to identify the most dominating factor for surface roughness. A mathematical model is developed for a certain range of operational condition for predicting the surface roughness of the drilled hole. Response surface methodology (RSM) was employed for the whole experimental design. Statistical tools are used for best fitting the developed model and desirability analysis is coupled with it in order to find out the optimum cutting condition for which minimum surface roughness is achieved. [PUBLICATION ABSTRACT]