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研究生: 戴昕楷
Xin-Kai Dai
論文名稱: 預測CNC平面銑削之加工時間
Estimation of Machining Time for CNC Planar Milling
指導教授: 李維楨
Wei-chen Lee
口試委員: 李維楨
Wei-chen Lee
石伊蓓
Yi-Pei Shih
魏振隆
Chen-Lung Wei
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 84
中文關鍵詞: 銑削加工時間預測迴歸分析
外文關鍵詞: Milling, Machining time, Prediction, Regression analysis
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  • 為了面對少量與多樣化的生產線,如果能準確地預測CNC加工機的切削時間,能在有限的資源與生產能力下將生產線的時間排程更緊密、提升機台的稼動率與更準確的評估生產成本。
    本研究利用馬達控制方法中的加減速規則與實際機台優化路徑方式預測CNC機台加工時間,利用myRIO上的加速規找到機台加加速度參數代入由運動學推導的加工時間計算式,用迴歸分析建立優化路徑加工時間與進給跟路徑夾角的關係式,建立模型預測CNC平面銑削之加工時間。實驗設備為東台精機的立式五軸CNC銑削加工機,以X軸向與XY平面的簡單幾何路徑實驗歸納出預測加工時間模型。使用本研究的模型預測在不同的平面上兩種路徑規劃方式進行平面銑削的切削路徑的加工時間,其平均誤差為9%。


    To meet the challenge of small volume production, we need to accurately predict the CNC machining time so that we can have a tighter schedule, a higher machine utiliza-tion rate, and a more realistic estimate of the machining cost. The objective of this re-search was to build a model to predict the planar machining time accurately. First, we used the accelerometer to measure the jerk of a CNC machine in the machine shop. Then, we applied the jerk to the machining time equations for the long path we derived. We also used regression analysis to generate the machining time equation for the short path at the corner of two paths. These two equations were adopted as the CNC ma-chining time prediction model. The average error of using the model was 9%.

    摘要 I Abstract II 誌謝 III 目錄 IV 圖目錄 VI 表目錄 VIII 第一章 緒論 1 1.1 研究背景與動機 1 1.2 文獻探討 1 1.3 研究目的 10 第二章 實驗設備與實驗方法 11 2.1 實驗設備 11 2.2 實驗方法 13 2.2.1 CNC馬達控制之加減速規劃 13 2.2.2 CNC機台加加速度參數 14 2.2.3 迴歸分析 18 2.2.4 插補點與夾角關係 19 2.2.5 CNC實驗機台優化路徑方式 19 第三章 加工時間預測方法 22 3.1 長路徑加工時間公式推導 22 3.2 短路徑加工時間公式推導 24 第四章 實驗結果 27 4.1 利用計算式預測加工時間與誤差比較 27 4.1.1 X軸向長加工路徑 27 4.1.2 X軸向短加工路徑 28 4.1.3 XY平面之簡單幾何路徑 30 4.1.4 XY平面之圓弧形加工路徑 35 4.1.5 XY平面連續短路徑之插補方式 38 4.2 加工參數對預測時間誤差之相關係數分析 39 第五章 加工時間預測模型 42 5.1 預測加工時間模型程式介紹 42 5.1.1 匯入G code檔案 42 5.1.2 讀取加工資訊 43 5.1.3 添加插補座標點 43 5.1.4 短路徑插補修正 45 5.1.5 計算加工時間 45 5.2 預測加工時間模型在實際切削路徑資料的表現 46 第六章 結論與未來展望 50 6.1 結論 50 6.2 未來展望 51 參考文獻 52 附錄 54

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