"There is an increasing demand by medical, energy, commercial and aerospace applications for miniature parts with micro-scale features. Being a versatile way of fabricating micro-scale parts on a wide range of materials, mechanical micro-machining can effectively address the demand. In micro-machining, features are machined by mechanically removing material from the workpiece using micro-scale cutting tools (micro-endmills, micro-drills, micro-grinders) rotated with high speeds. To have a better control on dimensional accuracy, and to have savings in space, power and cost, micro-machining is performed on miniature machining centers (MMCs). Micro-machining cannot be utilized with its true potential today since the repeatability and efficiency of the micro-machining processes are limited due to the static and dynamic deflections (vibrations). The research objective of this proposal is to improve the accuracy and repeatability of mechanical micro-machining processes by incorporating model-based predictive control to MMCs. Model predictions will be used to drive the MMC actuators to minimize the static and dynamic deflections during micro-machining. The controller will calibrate the model parameters according to sensor measurements of tool deflection and cutting forces. The performance of the intelligent micro-machining process (IMMP) will be evaluated by fabricating micro-scale features on a wide range of materials. The subject of this proposal is novel since it will be the first attempt to perform research in application of model-based predictive control in mechanical micro-machining. If the project becomes successful, accurate and repeatable intelligent machining processes will be developed, and will be used for fabricating micro-scale parts."