Sculptured surface machining (SSM) is one of the continually used manufacturing processes for die/mold, aerospace(especially turbine blades), precision machine design, bio-medical devices and automotive industries. Developments of machining technologies for quality enhancement of machining results has become a very important fact in current real industry. Off-line feedrate adjusting is a new methodology to automatically decide optimum feedrates for G-code modification. Off-line re-adjusting feedrates based on changing surface geometry (concave, convex and flat surface) in sculptured surface machining could decrease milling time, reduce tool wear, deflection and improve surface texture quality. Monitoring of sculptured surface milling processes is a critical requirement in the implementation of any unmanned operation in a shop floor. During the last years, notable efforts have been made to develop reliable and robust monitoring systems based on different types of sensors such as cutting force and torque, motor current and effective power, vibrations, acoustic emission or audible sound energy. In automated machining processes, condition monitoring not only reduces the production costs by reducing downtime and unnecessary tool changes, but also improves the product quality by eliminating chatter and poor surface finish. This study examines the possibility of using sound pressure level to monitor the sculptured surface milling process at different machining conditions and to evaluate MRR based feedrate optimization applications. In this paper, audible sound is investigated as a dynamic approach is established to enhance our understanding of the relationship among cutting conditions, tool deflection, cutting forces and the sound signal generated from the cutting process.