本研究揭示了一種涉及金屬塑性變形製程之自動化系統開發方法，嘗試為小型船用螺旋槳生產過程中，以往只能由人工針對葉片邊緣位置進行的手動校正製程，開發一套可由機器執行的自動化校正系統。本系統將能夠自動判斷螺旋槳不同歪斜量與其分布情形，並採取專家系統策略對葉片施加校正，以突破國內螺旋槳葉片校正無法自動化之瓶頸。
本系統於軟硬體建置階段，利用有限元素法與CAE結構分析技術，對螺旋槳葉片進行彈塑性分析，模擬螺旋槳校正過程中，螺旋槳葉片受到強制位移後，所產生之強制位移量與永久形變量，並使用分析結果建立一數學模型，存放於專家系統之知識庫中供未來校正時調用。本系統與數值控制設備進行資料交換，接收到來自數控設備之螺旋槳歪斜量分布之後，能夠透過演算法，計算出當前應採取之校正策略、螺旋槳葉片上應優先校正之範圍與建議校正量。在每次校正完成後，藉由數值控制設備回授之真實形變量即時修正知識庫中之數學模型，當系統之校正經驗逐漸增加，數學模型亦越貼近真實情形，從而加提升設備校正效率。硬體部分，結構分析模擬對機構設計起到輔助作用，並提供結構剛性分析與零件材料選用之方向。
本系統透過對數片螺旋槳葉片進行實驗驗證系統功能，結果顯示，本系統之演算法對於不同歪斜量分布情形之螺旋槳葉片，都能提供良好之校正決策，並將其全數校正至設定之公差範圍內，且透過本系統校正完成之螺旋槳葉片之尺寸精度(Cp)與準度(Ca)指標，皆有顯著提升。最後，藉由本系統之附屬程式，能夠產出校正品質之分析圖表，進而提供一種使管理方能以透過量化、可視化之資料，決定未來製程改良方向之指標。

In this research, a method of manufacturing automation involving plastic analysis and prediction of metals is developed. A small-sized marine propeller blade measurement and shape-correction expert system is proposed, which is designed to be connected to the NC propeller blade inspection and the shape correcting machine in order to solve the problem of the dependence on manual workers due to the fact of that propeller blade alignment process was conducted exclusively by manual operations.
The propeller blade alignment process involves plastic deformation of metal blades, which can be analyzed by Finite Element Analysis. In this research, we used ANSYS Workbench to simulate the elastoplastic problem of the propeller blade alignment. Based on the results of the simulations, a displacement-plastic deformation relationship can be derived as a mathematical model during the blade correcting process, so that the inference engine of the expert system can calculate by the deviation distribution data of a blade edge returned by the NC machine and give the NC machine a recommended value for the blade correction. During the building stage of the system, the results of the FEM simulations on propeller blades help designing a strong enough mechanism and the selection of the material of the NC machine. After a blade shape-correction process, an accessory program can produce a form and a histogram of the quality analysis, by which the management of the production can easily improve the pre-process of the propeller manufacturing.
To verify the capability of the expert system, several experiments have been conducted. In the first experiment, an optimal range of displacement values is recommended during the preliminary correction process. In the second experiment, the correction process was implemented on 15 different propeller blades. The results show that the algorithm of the system can complete the preliminary correction process in 3 rounds of corrections no matter how the initial deviations of the blade distribute. In the third experiment, the system continuously corrected one batch of 15 propeller blades, all of the blades were successfully corrected and fit the acceptance tolerance even though the initial precision and accuracy of the batch of propeller blades was poor.
In conclusion, the propeller correction expert system is reasonably reliable and effective on the reduction of human time and cost while assure the quality of the corrections. The experience stored in the knowledge base of the expert system can be easily duplicated and functioned disregards of who the machine operator is.

[1] B. Kehoe, S. Patil, P. Abbeel, and K. Goldberg, "A survey of research on cloud robotics and automation," IEEE Transactions on automation science engineering, vol. 12, no. 2, pp. 398-409, 2015.
[2] 謝宗恩, "六軸手臂自動循線運動系統開發," 碩士, 機械工程系, 國立臺灣科技大學, 台北市, 2018.
[3] 林冠甫, "基於影像伺服之輸送帶上物件自動追蹤系統," 碩士, 機械工程系, 國立臺灣科技大學, 台北市, 2016.
[4] A. S. Sabau, W. D. J. M. Porter, "Alloy shrinkage factors for the investment casting of 17-4PH stainless steel parts,", Metallurgical Materials Transactions B,vol. 39, no. 2, pp. 317-330, 2008.
[5] 江孟峰, 專家系統. 台灣: 文魁資訊股份有限公司, 2002.
[6] 張紹勳, 人工智慧與專家系統. 台灣: 松崗電腦圖書資料股份有限公司, 1993.
[7] V. Deslandres and H. Pierreval, "An expert system prototype assisting the statistical validation of simulation models," Simulation, vol. 56, no. 2, pp. 79-89, 1991.
[8] L. Huei-Huang, Finite Element Simulations with ANSYS Workbench 15. 台灣: 全華圖書股份有限公司, 2014.
[9] M. J. Bryant, H. P. Evans, and R. W. Snidle, "Plastic deformation in rough surface line contacts—a finite element study," Tribology International, vol. 46, no. 1, pp. 269-278, 2012.
[10] G. Meza, C. del Carpio, N. Vinces, and M. Klusmann, "Control of a three-axis CNC machine using PLC S7 1200 with the Mach3 software adapted to a Modbus TCP/IP network," in 2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON), 2018, pp. 1-4: IEEE.
[11] 楊榮顯, 工程材料學. 台灣: 全華圖書, 2012.
[12] 工藤英明, 塑性學. 日本: 森北出版, 1968
[13] A. Mamun, R. Moat, J. Kelleher, and P. Bouchard, "Origin of the Bauschinger effect in a polycrystalline material," Materials Science and Engineering, vol. 707, pp. 576-584, 2017.
[14] G. J. Hwang and S. S. Tseng, "On building a medical diagnostic system of acute exanthemas," Journal of the Chinese Institute of Engineers, vol. 14, no. 2, pp. 185-195, 1991.
[15] T. W. Kirkman. (1996). Least Squares Fitting (Regression).
[16] 劉晉奇 and 褚晴暉, 有限元素分析與ANSYS的工程應用. 台灣: 滄海書局, 2016.
[17] D. L. Logan, A first course in the finite element method. Cengage Learning, 2016.
[18] R.C.Hibbeler, Engineering Mechanics STATICS. U.S.A.: Pearson. 2017.
[19] Gere, J. M., Mechanics of Materials,6, Brooks/Cole, 2004.