MECHANICS, DYNAMICS AND CONTROL OF MACHINING SYSTEMS

机械加工是机械零件制造中应用最广泛的工序。昂贵的航空航天零件是通过去除90%的材料从实心块加工而成的。为了缩短加工时间，同时避免废品率，汽车行业大规模生产线的原型成本可达数百万美元。用于定向加工应用的计算机数字控制(CNC)机床的物理试验和样机是昂贵和耗时的。该行业需要高效的加工策略，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。这项研究有助于对多轴加工操作及其与机床结构、运动学和控制系统的相互作用进行数学建模。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我们实验室开发的新型9轴高速高精度数控微型机。这台机器有三个直线电机驱动的轴，一个磁悬浮转盘放置在平移工作台上。将对机器的运动学进行建模，在同时控制9个驱动器的情况下，将准确地提供5个自由度的运动。该机器将在模具和模具的5轴微球磨以及塑料的3D打印中进行测试。将运动学知识应用于工业中广泛使用的五轴数控车床的建模。加工动力学的研究将重点放在切削力、扭矩、功率和振动的预测上，以模拟和优化数字化环境下的车削和薄壁零件加工操作。薄壁零件在加工过程中会经历剧烈的颤振，这会导致表面质量差和公差超标，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。对每个材料去除步骤的零件动力学进行数值模拟，需要从结构的大刚度和大质量矩阵中求解一个特征值问题。因此，它在生产中的使用时间是非常紧迫的。这项研究将研究沿刀具路径的刀具接触区域零件的结构动力学模型的解析和快速更新。该方法将应用于喷气发动机叶片的5轴球头铣削和油气输送管道的螺纹车削。*提出的研究将丰富现有的加工知识，实现完整的、基于科学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.