CAREER: Measurement and Predictive Dynamics of Meso-scale Milling

职业：细观铣削的测量和预测动力学

• 批准号: 0757776
• 负责人: Brian Mann
• 金额: --
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-31 至 2010-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0757776&HistoricalAwards=false
• 关键词: CAREER; Measurement; Predictive; Dynamics; Meso

The research objective of this Faculty Early Career Development (CAREER) Program project is to develop analysis and sensing methods for conventional to miniature milling dynamics; these developments will enable Smart Machine Tools that account for the effects of vibration. Current methods for predicting the dynamic behavior of the milling process are limited because they do not provide combined stability and accuracy information. Therefore, the selection of machining parameters is commonly based upon limited information or experience. The result is unnecessary part errors that are created from tool vibrations. These errors are a limiting factor when producing precision components (e.g. thin wall structures and miniature components). Tool vibrations impose severe limitations on industrial capability: 1) reduced accuracy; 2) a poor surface finish; and 3) increased costs which are linked to instability. Although research studies target these limitations for conventional size tools, the differences and role of dynamics at miniature levels has remained virtually unstudied. Dynamical system analysis and modeling efforts provide the crucial first steps for integrating control strategies into smart machines.If successful, this research will advance industrial capability for conventional to miniature machining applications, develop new capabilities for monitoring rotating shaft motions, and provide advances in miniature part production (e.g. small medical devices and MEMS). Outreach and recruiting efforts focus on K-12 students and undergraduate students, particularly from traditionally underrepresented groups, through: 1) developing a "So you want to be an engineer?" outreach program with a hands-on children's learning museum; 2) two existing UF outreach programs. Furthermore, this research develops tools that enhance the infrastructure for future research and seeks to enable the industrial application of miniature machining dynamics.

该学院早期职业发展（CAREER）计划项目的研究目标是开发传统到微型铣削动力学的分析和传感方法;这些发展将使智能机床能够考虑振动的影响。当前用于预测铣削过程的动态行为的方法是有限的，因为它们不提供组合的稳定性和准确性信息。 因此，加工参数的选择通常基于有限的信息或经验。 结果是由刀具振动产生的不必要的零件误差。 这些误差是生产精密部件（例如薄壁结构和微型部件）时的限制因素。工具振动对工业能力造成严重限制：1）精度降低; 2）表面光洁度差;以及3）与不稳定性相关的成本增加。 虽然研究针对传统尺寸工具的这些限制，但在微型水平上的动力学差异和作用实际上仍未得到研究。 动态系统分析和建模工作为将控制策略集成到智能机器中提供了关键的第一步。如果成功，这项研究将提高传统到微型加工应用的工业能力，开发监控旋转轴运动的新功能，并促进微型零件生产（例如小型医疗设备和MEMS）。 外联和招聘工作的重点是K-12学生和本科生，特别是来自传统上代表性不足的群体，通过：1）制定一个“所以你想成为一名工程师？“外展计划与动手儿童学习博物馆; 2）两个现有的用友外展计划。 此外，这项研究开发的工具，加强基础设施，为未来的研究，并寻求使微型加工动力学的工业应用。