This thesis presents a study into the enhancement of productivity in micromilling processes by considering a fundamental treatment of tool path trajectory generation techniques and process optimization strategies that account for the impact of scale effects present in high-speed, high-precision micromachining operations. Micromilling is increasingly applied to the production of a wide variety of micro components, due to its high precision and flexibility. However, the productivity of micromilling is limited by the low feedrates necessitated by the inherent high precision and small feature size. In this study, several scale effects present at the microscale are identified, in particular the increase of the ratio of tool size to feature size, and the corresponding impact on trajectory generation and process optimization is investigated. The scale effects are shown to cause increased geometric error when the standard method of VF-NURBS is applied to microscale feedrate optimization. The method of Enhanced Variable-Feedrate NURBS (EVF-NURBS) is proposed and shown to successfully compensate for the scale effects leading to reduced geometric error. A key contribution of this study is the construction and experimental validation of the Variable-Feedrate Intelligent Segmentation (VFIS) method for increased feedrates and improved stability. The VFIS method provides a cutting time reduction of more than 50% in some cases, while effectively constraining geometric error. Two tool size optimization schemes are presented for maximizing productivity and minimizing geometric error while accounting for dynamic effects uniquely present at the microscale. Finally, the development of a low-cost, high-precision micro-mesoscale machining center (mMC) is presented.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/31764 |
| Date | 16 November 2009 |
| Creators | Sodemann, Angela Ann |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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