MECHANICS, DYNAMICS AND CONTROL OF MACHINING SYSTEMS

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Machining is the most widely used operation in manufacturing mechanical parts. Costly aerospace parts are machined from solid blocks by removing 90% of the material. Prototyping costs of mass production lines in the automotive industry can reach a few million dollars in order to shorten the machining time while avoiding scrap rates. The physical trial and prototyping of Computer Numerical Control (CNC) machine tools for targeted machining applications are costly and time consuming. The industry needs productive machining strategies to stay competitive by predicting the physical performance of manufacturing steps ahead of costly physical trials. This research contributes to the mathematical modeling of multi-axis machining operations and their interaction with machine tool structures, kinematics, and control systems. The mathematical models will be used to predict the outcome of the machine design and manufacturing scenarios, which will enable the engineer to optimize manufacturing operations. ***The kinematics and control research will be based on a novel, 9 axis, high speed – high precision CNC Micro Machine developed in our laboratory. The machine has three linear motor driven axes with a magnetically levitated rotary table placed on a translational table. The machine's kinematics will be modeled, and 5 degrees of freedom motion will be delivered accurately while controlling 9 drives simultaneously. The machine will be tested in 5 axis micro-milling of dies and molds, as well as in 3D printing of plastics. The kinematics knowledge will be applied in modeling 5-axis CNC mill-turn machines which are widely used in the industry. The research in machining dynamics will focus on the prediction of cutting forces, torque, power and vibrations to simulate and optimize mill-turning and thin walled part machining operations in a digital environment. The thin walled parts experience severe chatter vibrations during machining which leads to poor surface quality and tolerance violations, hence limiting the productivity. As the material is removed during the machining, the mass and stiffness of the parts change continuously. Numerical modeling of part dynamics at each material removal step requires the solution of an eigenvalue problem from large stiffness and mass matrixes of the structure. Therefore, it is time prohibitive for use in production. This research will investigate the analytical and rapid updating of the structural dynamic models of the parts at tool – workpiece contact zones along the tool path. The proposed method will be applied in 5 axis ball end milling of jet engine blades and thread turning of oil-gas transportation pipes. ***The proposed research will enrich the current knowledge in machining to achieve complete, science and physics based digital machining technology.