The introduction of multi-axis CNC machining has reduced machining time and increased production rates. However, optimizing simultaneous operations to produce quality parts and prolong tool life still possesses a challenge to engineers due to the mutual interactions of two tools removing material and the amount of factors and noise in a production environment. Since there are multiple factors and the sources of error are unknown, we use a statistical approach to obtain and organize information. A design of experiment study was implemented across twelve sensor responses to optimize the spindle speed, feed rate, inner diameter (ID) depth of cut and outer diameter (OD) depth of cut for simultaneous turning and boring roughing operations. The optimal machining conditions were obtained by a response optimizer from Minitab 16 statistical software. The optimized settings result in 13% reduced cutting and 10% reduced total power consumption for a 3% increase of average power. Future studies will cross correlate different responses to reduce the number of sensors in developing a robust adaptive controller for chatter detection and tool condition monitoring.

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