At present, the machine tool technology in the US is not in the state-of-the-art of leading international competitors. Conventional machine tools under use are being pushed into their machining accuracy limits. There is a pressing need calling for revitalizing the machine tool industry. This paper presents, a mechatronic system developed for reducing tool vibration during machining. It consists of electrical and mechanical components, and is realized by placing electrically driven electrostrictive actuators in a specially designed tool post mechanical structure. The linear neural network controller, namely, digital filters, are implemented using a signal processing board. The experimental investigation is conducted in two stages. In the first stage, a test bed is established to use an electro-magnetic shaker to resemble the excitation of cutting force acting on the tool. In the second stage, experiments were conducted using a lathe on the shop floor. In-process vibration cancellation was observed. In the laboratory experiment, a percent reduction in the 90 percent was possible using a feedforward scheme. The improvement in surface roughness during the turning operation was confirmed from measurements of surface roughness profiles.