In this research, the integration of the servomechanism control and process control for machining processes has been studied. As enabling strategies for next generation quality control, process monitoring and open architecture machine tools will be implemented on production floor. This trend brings a new method to implement control algorithm in machining processes. Instead of using separate modules for servomechanism control and process control individually, the integrated controller is proposed in this research to simultaneously achieve goals in servomechanism level and the process level. This research is motivated by the benefits brought by the integration of servomechanism control and process control. Firstly, the integration simplifies the control system design. Secondly, the integration promotes the adoption of process control on production floor. Thirdly, the integration facilitates portability between machine tools. Finally, the integration provides convenience for both the servomechanism and process simulation in virtual machine tool environment. The servomechanism control proposed in this research is based on error space approach. This approach is suitable for motion control for complex contour. When implement the integration of servomechanism control and process control, two kinds of processes may be encountered. One is the process whose model parameters can be aggregated with the servomechanism states and the tool path does not need real time offset. The other is the process which does not have direct relationship with the servomechanism states and tool path may need to be modified real time during machining. The integration strategies applied in error space are proposed for each case. Different integration strategies would propagate the process control goal into the motion control scheme such that the integrated control can simultaneously achieve goals of both the servomechanism and the process levels. Integrated force-contour-position control in turning is used as one example in which the process parameters can be aggregated with the servomechanism states. In this case, the process level aims to minimize cutting force variation while the servomechanism level is to achieve zero contour error. Both force variation and contour error can be represented by the servomechanism states. Then, the integrated control design is formulated as a linear quadratic regulator (LQR) problem in error space. Force variation and contour error are treated as part of performance index to be minimized in the LQR problem. On the other hand, the controller designed by LQR in error space can guarantee the asymptotic tracking stability of the servomechanism for complex contour. Therefore, the integrated controller can implement the process control and the servomechanism control simultaneously. Cutter deflection compensation for helical end milling processes is used as one example in which the process cannot be directly associated with the servomechanism states. Cutter deflection compensation requires real-time tool path offset to reduce the surface error due to cutter deflection. Therefore, real time interpolation is required to provide reference trajectory for the servomechanism controller. With the real time information about surface error, the servomechanism controller can not only implement motion control for contour requirement, but also compensation for the dimensional error caused by cutter deflection. In other words, the real time interpolator along with the servomechanism controller can achieve the goals of both the servomechanism and process level. In this study, the cutter deflection in helical end milling processes is analyzed first to illustrate the indirect relationship between cutter deflection and surface accuracy. Cutter deflection is examined for three kinds of surfaces including straight surface, circular surface, and curved surface. The simulation-based deflection analysis will be used to emulate measurement from sensors and update the real-time interpolator to offset tool path. The controller designed through pole placement in error space can guarantee the robust tracking performance of the updated reference trajectory combining both contour and tool path offset required for deflection compensation. A variety of cutting conditions are simulated to demonstrate the compensation results. In summary, the process control is integrated with the servomechanism control through either direct servomechanism controller design without tool path modification or servomechanism control with real time interpolation responding to process variation. Therefore, the process control can be implemented as a module within machine tools. Such integration will enhance the penetration of process control on production floor to increase machining productivity and product quality.