| Author: | Kong, Lingbao |
| Title: | Modeling of ultra-precision raster milling and characterization of optical freeform surfaces |
| Degree: | Ph.D. |
| Year: | 2010 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Machining Milling machinery. Optical instruments Surfaces (Technology) |
| Department: | Department of Industrial and Systems Engineering |
| Pages: | xviii, 255, 5 leaves : ill. ; 31 cm. |
| Language: | English |
| Abstract: | Ultra-precision raster milling is an enabling technology for machining freeform optical surfaces with submicrometric form accuracy and nanometric surface finish without any subsequent processing. Currently, the achievement of a super mirror finish still relies largely on the experience and skill of the machine operators through an expensive trial-and-error approach. Due to the geometrical complexity of the surfaces, there is still a lack of surface characterization methods to measure the ultra-precision freeform surfaces. There is a need for the development of theoretical models and systems to predict, simulate and characterize the surface generation in the ultra-precision raster milling of optical freeform surfaces. In the present study, the research work has been divided into three parts. The first part consists of a theoretical and experimental investigation of the factors affecting the surface roughness in ultra-precision raster milling. Various surface roughness models have been built based on the cutting mechanics, surface generation mechanisms and cutting strategies. These models were experimentally verified through a series of cutting experiments. The results not only provide an important means for better understanding the surface generation in ultra-precision raster milling, but also provide the basis for the establishment of a model-based simulation system for the prediction and optimization of surface generation in ultra-precision raster milling. In the second part, a series of novel methods for the measurement and form characterization of ultra-precision freeform surfaces has been established, including the Integrated Freeform Characterization Method (IFCM), the Robust Freeform Characterization Method (RFCM), the Coupled Reference Data Freeform Evaluation Method (CRDM), as well as the Hybrid Fitting and Matching Method (HFMM). The IFCM employs an escalating approach to matching the measured data to the design model through the rough matching of defined surface feature data, followed by fine matching based on the least-squares and minimum zone criteria. The RFCM is an extension of the IFCM incorporating a robust algorithm to deal with the outliers. For some flat freeform surfaces with weak features, the CRDM uses the coupled reference data to localize the surface of the workpiece. The HFMM combines the fitting and matching approaches for the form characterization of ultra-precision freeform surfaces when there is no reference data or design model provided. A number of freeform surface characterization systems have been built based on these methods and they have been verified through a series of computer simulations and measurement experiments. The results indicate that the developed freeform surface characterization methods and systems can realize precise measurement and characterization of ultra-precision freeform surfaces with form accuracy down to the sub-micrometer range. In the third part of the study, a model-based simulation system has been established for the prediction and optimization of form generation in ultra-precision raster milling. It takes into account different factors which affect the surface generation such as the cutting mechanisms, tool path and the cutting process. Moreover, the system has been built using a series of deterministic models including a Tool Path Generation Model (TPGM), an Overcut Detection Model (ODM), and an Integrated Kinematic Error Model (IKEM). In the TPGM, the tool nose radius and swing distance are compensated for and hence the tool path is generated according to the surface residual error requirements. Before the simulation of surface generation, a surface overcut is first detected using the ODM. The IKEM has been built after a comprehensive consideration of machine tool kinematic errors, as well as of the process of surface generation. The IKEM makes use of the overall motion errors of the slides to predict the freeform errors. The successful establishment of the model-based simulation system forms the theoretical basis for the later study of optimization of ultra-precision raster milling. The optimization of ultra-precision raster milling includes the optimization of machining parameters, cutting strategies and kinematics errors. The performance of the system has been successfully verified through a series of cutting experiments on different freeform surfaces. The successful development of the analytical models and the model-based simulation system helps to make the ultra-precision raster milling process more predictive, and also allows the surface generation and cutting strategies to be optimized without the need for conducting expensive and time consuming trial-and-error cutting tests. The present study not only contributes significantly to the modeling and optimization of surface generation in ultra-precision raster milling of optical freeform surfaces, but also contributes to the advancement of the science and technology of measuring ultra-precision freeform surfaces. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b23745095.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.99 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/5782