Milling is the most widely applied machining process for producing flat surfaces and prismatic shapes. To minimize the process time and maximize the quality of the workpiece, it is essential to monitor the condition of cutting tool in machining operation and to optimize the process parameters. In the present investigations, experiments were performed on EN31 steel with un-coated carbide inserts in face milling with tools having different approach angles in order to determine the performance of the tool. The effects of process parameters namely speed, depth of cut and feed on tool wear of work piece were investigated. The cutting forces and tool wear are measured in order to evaluate the performance of the cutter. Acoustic emission signal was used for the online tool monitoring. A statistical technique, Taguchi design of experiments was used to optimize the machining process parameters such as speed, feed, depth of cut and approach angle.