MECHANICS, DYNAMICS AND CONTROL OF MACHINING SYSTEMS

机械加工是制造机械零件中使用最广泛的操作。昂贵的航空航天零件是从固体块通过去除90%的材料加工而成的。汽车工业中大规模生产线的原型成本可能达到数百万美元，以缩短加工时间，同时避免废品率。用于目标加工应用的计算机数控（CNC）机床的物理试验和原型制作成本高且耗时。该行业需要高生产率的加工策略，通过在昂贵的物理试验之前预测制造步骤的物理性能来保持竞争力。这项研究有助于多轴加工操作的数学建模及其与机床结构，运动学和控制系统的相互作用。数学模型将用于预测机器设计和制造方案的结果，这将使工程师能够优化制造操作。 运动学和控制研究将基于本实验室开发的新型九轴高速高精度数控微加工机床。该机器有三个直线电机驱动轴，磁悬浮旋转台放置在平移台上。机器的运动学将被建模，5个自由度的运动将被精确地传递，同时控制9个驱动器。该机器将在模具和模具的5轴微铣削以及塑料的3D打印中进行测试。运动学知识将应用于工业中广泛使用的五轴数控车铣复合机床的建模。加工动力学的研究将集中在切削力，扭矩，功率和振动的预测，以模拟和优化铣削车削和薄壁零件加工操作在数字环境中。薄壁零件在加工过程中会经历严重的颤振，导致表面质量差和公差违规，从而限制了生产率。随着材料在加工过程中被去除，零件的质量和刚度不断变化。在每个材料去除步骤的零件动力学的数值建模需要从结构的大刚度和质量矩阵的特征值问题的解决方案。因此，在生产中使用时，时间是不允许的。研究了刀具轨迹沿着刀-工接触区零件结构动力学模型的解析和快速修正方法，并将该方法应用于喷气发动机叶片的五轴球头立铣和油气输送管道的螺纹车削。 该研究将丰富现有的加工知识，实现完整的，科学的和物理的数字化加工技术。

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.