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研究生： 黃建峰
Huang, Jian-Feng
論文名稱： 自由曲面五軸機器人自動化模具拋光之研究
Automatic Mold Polishing for Free-Form Surfaces by Using a Five-Axis Robot
指導教授： 蔡明俊
Tsai, Ming-June
學位類別： 博士
Doctor
系所名稱： 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年： 2005
畢業學年度： 93
語文別： 英文
論文頁數： 110
中文關鍵詞： 路徑規劃 、模具拋光 、自動化拋光 、均勻磨耗模式 、自由曲面 、排程規劃
外文關鍵詞： Automatic polishing, Process planning, Path planning, Free-form surface, Uniform wearing model, Mold polishing
相關次數： 點閱：144  下載：9 
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    • 　　本研究中加強了一個自動化模具拋光系統(Automatic Mold Polishing System, AMPS)的功能。此系統包括了四個主要的模組：幾何模組、路徑規劃模組、排程規劃模組與拋光執行模組。幾何模組方面，本研究中的B-spline自由曲面幾何為IGES (Initial Graphics Exchange Specification)檔案格式。在讀入B-spline自由曲面的參數之後，AMPS會根據這些曲面參數重建一個曲面並繪出在使用者視窗介面中，然後藉著B-spline自由曲面的微分幾何特性求出法向量、主曲率與有效接觸面積等重要的拋光參數。拋光路徑規劃方面，掃描旋擺路徑(scan-weaving path)與碎形旋擺路徑(Peano-weaving path)同樣也可以根據B-spline自由曲面的參數將路徑點產生在三維的自由曲面上。在產生三維路徑點的同時也考慮了均勻磨耗的問題，而此均勻磨耗的模式是架構在等拋光力量與有效接觸面積理論之上。在拋光排程方面，使用者輸入拋光的需求參數之後，AMPS就會根據排程資料庫中以最佳拋光參數為基礎的拋光效率曲線自動排出一個最佳拋光效率排程。其中這些最佳拋光效率曲線都是以田口式拋光實驗所求得。
    　　拋光執行方面，本研究中以具有力量控制能力的五軸機器人來執行，並以兩個光學模具為實驗驗証的對象，分別使用了不同的拋光排程與拋光路徑，比較兩者的拋光效果。研究的最後對於拋光排程的表面粗糙度達成率、表面輪廓與磨耗深度的預測公式都進行了分析與驗証。結果顯示此效率曲線排程具有良好的表面粗糙度達成率。而使用碎形旋擺路徑所拋出來的表面輪廓則比使用掃描旋擺路徑的輪廓來得平滑。磨耗深度預測公式也被証明具有高度的準確性。

    　This thesis enhances the automatic mold polishing system (AMPS) developed by the Robotics and Automation Laboratory, NCKU. In which four major modules are integrated to accomplish the goal of automatic polishing. These modules are: (1) the mold geometry kernel module, (2) the path planner module, (3) the process planner module, and (4) the polishing execution module. In new version of AMPS system, the free-form surfaces in IGES format are read and the mold geometry regenerated as a B-Spline surface. Using the derivative properties of the B-Spline surface, the normal vector, the principal curvatures, and the effective contact area can be calculated at any point on the surface. The polishing paths are generated and drawn on the 3D mold surface for verification. A uniform wear model is developed based on the effective contact area with constant pressure control. According to the polishing requirements of the mold, AMPS automatically schedules the polishing process using polishing efficiency based on sets of optimal polishing parameters determined from Taguchi experiments.
    　Using a five-axis force-controlled robot developed by our laboratory, two optical molds are polished using the scan-weaving and Peano-weaving path generation methods, respectively. The experimental results show that the final surface roughness of both molds satisfies the expectations specified in the respective process plans. The surface profiles of the two molds are analyzed and compared. It is found that the surface profile of the mold polished with the Peano-weaving path is superior to that of the mold polished using the scan-weaving path. The material removal is also analyzed to validate the proposed uniform wear model. The results confirm that this model provides highly accurate predictions of the material removal and polishing time.

    Abstract (Chinese) I Abstract II Acknowledgements (Chinese) III Acknowledgements IV List of Figures VIII List of Tables XI Nomenclature XIII Chapter 1 Introduction 1 1.1 Motivation and purpose 1 1.2 Literature review 2 1.3 Outline 3 Chapter 2 Polishing Process Parameters and System Configuration of the Automatic Mold Polishing System 5 2.1 Standard polishing tools and processes 5 2.1.1 Tool types 5 2.1.2 Grinder types 6 2.1.3 Standard processes 6 2.2 Polishing parameters 8 2.2.1 Grain size 9 2.2.2 Polishing pressure 9 2.2.3 Tool rotational speed 9 2.2.4 Ring diameter 10 2.2.5 Weaving path parameters 10 2.2.6 Polishing path cycle 12 2.3 AMPS system 12 2.3.1 Create a polishing project and inputting mold data 12 2.3.2 The user interface and geometry kernel module 14 2.3.3 The process planner module 16 2.3.4 The path planning module 17 2.3.5 The polishing execution module 19 2.4 System hardware 20 Chapter 3 Determine Optimal Polishing Parameters Using the Taguchi Method 24 3.1 A new polishing tool 24 3.2 Determination of optimal polishing parameters using the Taguchi method 25 3.2.1 Taguchi orthogonal arrays 26 3.2.2 The S/N ratio of each trial run 27 3.2.3 Analysis of variance 28 3.3 Experimental results 29 3.4 The polishing efficiency curve and procedure scheduling 33 3.4.1 Polishing curves 33 3.4.2 Automatic process planning 34 3.4.3 Modified process by adding diamond paste with the new tool 39 Chapter 4 Uniform Material Removal Model 41 4.1 Uniform wearing model and uniform material removal control concept 41 4.2 Material removal experiment 42 4.2.1 Taguchi schedule for material removal experiments 42 4.2.2 Material removal experiment results 44 4.3 Effective contact area 48 4.3.1 Curvature analysis 48 4.3.2 Calculation of contact width 49 4.3.3 Contact area 52 4.3.4 Stability of contact 56 4.4 Contact width experiment 57 4.4.1 Experimental schedule and setup 58 4.4.2 Experimental results 59 Chapter 5 Path Planning for Free-Form Surfaces 61 5.1 Scan-weaving path 61 5.1.1 Generating scan-weaving path 61 5.1.2 Normal vector generation 63 5.1.3 Smoothing the normal vector 65 5.2 Peano-weaving path 67 5.2.1 Determination of minimum contact width 67 5.2.2 Determination of Peano-weaving parameters 67 5.2.3 Variation in rotation of axis 1 of robot 72 Chapter 6 Polishing Experimental Results and Discussion 73 6.1 Polishing experiment 73 6.1.1 Polishing experiment I: Scan-weaving path with process I 73 6.1.2 Polishing experiment II: Peano-weaving path with process II 76 6.2 Evaluation of polishing results 82 6.2.1 Polishing evaluation criteria 82 6.2.2 Polishing evaluation of experiments I and II 83 6.3 Profile analysis 84 6.3.1 Schedule of profile measurement 84 6.3.2 Smoothness analysis compared with fitting curve 85 6.3.3 Profile analysis compared with IGES surface 89 6.4 Verification of uniform wearing model 94 6.4.1 Definition of the removal rate and removal depth on free-form surface 94 6.4.2 Analysis and verification 95 Chapter 7 Conclusions and Recommendations 99 7.1 Conclusions and discussion 99 7.2 Recommendations and future studies 100 Reference 102

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