After well known formula relating tool life to cutting speed given by Taylor in 1907, a lot of research on the modelling and optimization of machining parameters for surface roughness, tool wear, forces, etc. has been done during last 100 years. However, a little research has been done to optimize the energy efficiency of machine tools. The energy efficiency of machines tools is generally very low particularly during the discrete part manufacturing. Reduction in power consumption, in addition to economical benefits, will also improve the environmental impact of machine tools and manufacturing processes. However, sustainability performance may be reduced artificially by increasing the surface roughness as lower surface finish requires lesser power and resources to finish the machining. But this may lead to more rejects, rework and time. Therefore, an optimum combination of power and surface finish is desired for sustainability performance of the machining processes. There is a close interdependence among productivity, quality and power consumption of a machine tool. The surface roughness is widely used index of product quality in terms of various parameters such as aesthetics, corrosion resistance, subsequent processing advantages, tribological considerations, fatigue life improvement, precision fit of critical mating surfaces, etc. But the achievement of a predefined surface roughness below certain limit generally increases power consumption exponentially and decreases the productivity. The capability of a machine tool to produce a desired surface roughness with minimum power consumption depends on machining parameters, cutting phenomenon, workpiece properties, cutting tool properties, etc. The first step towards reducing the power consumption and surface roughness in machining is to analyze the impact of machining parameters on power consumption and surface roughness. The results reveal that the developed predictive models provide a close relation between the predicted values and the experimental values for surface roughness and power consumption. The optimal machining parameters indicate that feed is the most significant machining parameter followed by depth of cut and cutting speed to reduce power consumption and surface roughness simultaneously. The optimization of machining parameters for minimum power requirement and surface roughness is expected to lead to the application of lower rated motors, drives and auxiliary equipments and hence save consumption of power not only during machining but as well as during build-up to machining, post machining and idling conditions.