Increasing the quality of a machined product and minimizing energy consumption is a primary objective for all industries, given their significant impact on manufacturing costs and the environment. The choice of the machining process and the optimal cutting parameters to meet this requirement is the objective of this experimental study, which deals with the effects of the cutting parameters and the machining process on the energy consumption and surface condition during the milling of AISI 304L austenitic steel. This article presents a multi-objective optimization method based on the response surface methodology and Grey's weighted relational analysis. Based on this approach, the down milling cutting parameters indicate that the cutting speed is the most influential parameter on energy consumption (62.71%), while the feed rate is the most influential factor in roughness (47.20%). For up milling, the cutting speed is the most important factor influencing surface roughness (29.07%) and also energy consumption (64.09%).It has also been found that the cutting power can be reduced by 39% for down milling and 16% for up milling compared to the maximum value. On the other hand, the quality of the machined surface can be improved by 58.5% for down milling and by 60% for up milling.