| 研究生: |
陳玉容 Yu-Rong Chen |
|---|---|
| 論文名稱: |
利用灰色關聯分析法探究線切割放電於SKD61加工之最佳化參數 Gray Relational Analysis to Explore the Optimal Process Parameters of Wire Electrical Discharge Machining in SKD61 Processing |
| 指導教授: |
崔海平
Hai Ping Tsui |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系 Department of Mechanical Engineering |
| 論文出版年: | 2019 |
| 畢業學年度: | 107 |
| 語文別: | 中文 |
| 論文頁數: | 81 |
| 中文關鍵詞: | 田口式實驗法 、變異數分析 、灰色關聯分析 |
| 外文關鍵詞: | Taguchi Method, Analysis of Variance, Gray Relation Analysis |
| 相關次數: | 點閱:24 下載:0 |
| 分享至: |
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隨著市場快速的演變,加工生產產品有日趨多樣少量且更新週期越短之模式,為能縮短研發時程且避免因設計錯誤而導致成本浪費,故本研究將針對線切割放電加工SKD61 材料之加工品質特性最佳化及多重加工品質特性分析進行研究。
本研究初始選擇使用田口式實驗法,規劃加工參數以及和該參數不同的水準條件,探討材料移除率、加工擴槽量及表面粗糙度等加工品質特性,經由變異數分析(ANOVA)的推算,分別獲致單因子加工品質特性之顯著加工參數與最佳化加工品質特性之參數組合條件。接者將前階段之田口式實驗法中單因子加工品質特性數據轉化並賦予熵權重,後續再整合灰色關聯分析而成為多重加工品質特性之評估值,進而獲致一最佳化加工參數之組合設定;此外,再代入原本18組數據資料中進行再次運算,驗證上述第19組為最佳化加工參數之組合。
實驗結果顯示,藉由整合灰關聯分析與田口式實驗法之分析,係為可快速獲取多重加工品質特性最佳化參數組合條件的方法。
The requirements of manufacturing products are shorter product cycles and less production lot in the rapidly changing modern market. It is benefited for the companies that the new products can be provide to the market with fewer designing mistakes, shorter lead time and lower production costs. Recently, gray relational analysis (GRA) has been widely applied to estimate the optimal processing parameters with multiple quality characteristics. Therefore, the gray relational analysis was used in the study to optimal process parameters of WEDM in SKD61 processing.
The study on its early stage was based on the Taguchi method. The control factors and the levels of these control factors were identified after pre-experimental planning. The material removal rate, kerf loss and surface roughness are also analyzed. Through analysis of variance (ANOVA) and F statistic calculation, the significant control factors of each quality characteristic and the optimal combinations of control factors were obtained. The following steps were setting weight for each quality characteristic of the previous Taguchi method and estimating the optimal WEDM parameters with multiple quality characteristics. Optimal WEDM parameters can then be determined by the Taguchi method using the gray relational grade as the performance index. The original 18 sets of data were taken again for calculation with the 19th set of the parameters to verify that the 19th set of the parameters is optimal parameters. The verification experimental results show that optimal WEDM parameters can be determined by using the gray correlation analysis.
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