| 研究生: |
吳宏達 Wu, Hung-Ta |
|---|---|
| 論文名稱: |
結合田口與多屬性決策法求解多重品質特性之穩健設計-以鋰電池銲接製程為例 A Combined Taguchi and Multiple-Attribute Decision Making Methods in Solving a Multi-Response Robust Design Problem -A Case of Li-ion Battery Welding Process |
| 指導教授: |
楊大和
Yang, Ta-Ho |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 工程管理碩士在職專班 Engineering Management Graduate Program(on-the-job class) |
| 論文出版年: | 2015 |
| 畢業學年度: | 103 |
| 語文別: | 中文 |
| 論文頁數: | 47 |
| 中文關鍵詞: | 田口方法 、多屬性決策 、理想解類似度順序偏好法 、穩健設計 |
| 外文關鍵詞: | Taguchi Method, MDAM, TOPSIS, Robust Design |
| 相關次數: | 點閱:113 下載:12 |
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鋰電池因俱備了無污染、無記憶效應、循環壽命長等諸多優點,受到可攜式電子產品與電動車的青睞,應用範圍更涵蓋於通訊、民生、醫療、交通、航太、軍事等不同領域。但因為鋰電池的能量密度較高,若發生電池內部短路時,快速釋放的能量會提高電池爆炸的風險,因此鋰電池製程品質工程的良莠與否,對其使用安全性來說是至關緊要的。而鋰電池組裝製程中,負極柄銲接為相當重要的一環。良好且穩定的負極柄銲接品質,能夠確保銲接過程中不會產生金屬銲渣並使負極柄與鋼罐能緊密且牢固地融合,進而降低鋰電池內部短路的風險。
由於鋰電池負極柄銲接製程的品質績效是以銲接拉力、銲接黏料狀況、鋼罐銲點外觀來衡量其績效好壞,而常見的田口方法多應用於單一品質特性觀察值的績效衡量,因此本研究結合田口與多屬性決策中的理想解類似度順序偏好法來建構實驗模式,將案例製程中的9項控制因子各設定3個水準構置L27直交表,使用理想解類似度順序偏好法循序將三項品質特性的S/N比,綜合成單一品質衡量指標值,再依該指標轉換成各組實驗之因子反應圖表,由大至小的排列出9項控制因子對品質特性績效的影響,並分析出最佳參數組合,再進一步確認最佳參數之品質特性觀察平均值、綜合績效值、S/N比均優於原始參數組合,為案例製程之多重品質特性績效評估方法的穩健設計實務應用上,提供了標準化的架構流程與方法以及後續研究的參考依據。
The welding of negative tab plays a key role in the assembly process of lithium batteries. A welding process with good quality and high consistency will not produce metal slag and can facilitate the integration of negative tab and stainless can firm and tight so that the risk of
internal short circuit is further reduced.
This research combines Taguchi Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Multiple Attribute Decision Making (MADM) method to perform robust parameter design by building the experiment mode for the resistance welding process of the negative tab of lithium batteries. It sets three standards for each of the 9 control factors to construct the L27 factor orthogonal array table; take it into the experiment and acquire three quality factors: welding tension, welding material status and stainless can bottom
welding spot observation. Calculate the S/N ratio for each quality factor using Taguchi method’s larger-the-better property; calculate a single comprehensive quality indicator using TOPSIS method in sequence and transform the ratio to the response table for every experiment
according to such indicator to figure out the optimized parameter combination. This provides an effective method and a reference to the application of robust design practice for manufacturing cases.
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