Evaluation of the effects of machining parameters on MQL based surface grinding process using response surface methodology

Grinding is a precision machining process widely used for close tolerance and good surface finish. Due to aggregate of geometrically undefined cutting edges and material removal in the form of microchips, grinding requires more specific energy as friction is greater in the grinding interface. The optimum use and proper penetration of coolant is the prime requirement which is achieved by effective cooling and lubrication. In this research, a greater focus is on MQL technique, which is economical and eco-friendly. The paper presents important aspects of the grinding process considering the surface roughness and cutting force. The experiments were carried out on horizontal surface grinding machine using Response surface methodology (RSM). In addition, evaluation of grinding performance parameters like coefficient of friction, cutting forces, temperature and specific grinding energy for different machining environments has been discussed. The lowest surface roughness and coefficient of friction observed was 0.1236 mu m and 0.3906, respectively for MQL grinding, whereas lowest specific grinding energy was found as 18.95 N/mm(2) in wet grinding. The temperature recorded in MQL grinding was 29.07 degrees C, which is marginally higher than wet condition. The response obtained as cutting forces, temperature and surface roughness under MQL mode encourages its use for machining AISI D3 type material compared to other grinding environments. Mathematical modeling showing the relation between the factors and response variables was established using Response surface methodology. Regression analysis was performed to determine the accuracy of mathematical model, significant factors and interaction effects of parameters on responses.