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題名：The Optimal Parameters Design of Multiple Quality Characteristics for the Welding of Aluminum Magnesium Alloy
書刊名：品質學報
作者：張志平 引用關係
作者(外文)：Jhang, Jhy-ping
出版日期：2016
卷期：23:3
頁次：頁201-211
主題關鍵詞：多重品質特性；氬銲；類神經網路；理想解類似度順序偏好法；鋁鎂合金；Multiple quality characteristics；TIG；ANN；TOPSIS；Aluminum magnesium alloy
原始連結：連回原系統網址new window
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  • 被引用次數被引用次數:期刊(2) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:4
  • 點閱點閱:12
鋁鎂合金材料銲接雖然有許多優異機械性質，但在氬銲銲接上其可銲性之條件範圍狹窄會有接合介面和融熔銲道形成硬而脆的介金屬化合物的困難點，一般對於銲接參數設定並沒有公式可循，完全憑藉專家過去的知識和經驗來設定，一旦超出專家經驗範圍，便無法有效設定最佳參數，本研究將發展一套解決鋁鎂合金銲接板參數多重品質特性實驗設計問題，探討銲接非破壞性品質特性─銲道厚度、銲道寬度、深寬比以及破壞性品質特性─拉伸、衝擊值等五個銲接品質特性，再應用理想解類似度順序偏好法 (Technique for Order Preference by Similarity to Ideal Solution) 與倒傳遞類神經網路 (Artificial Neural Network) 搜尋最佳架構，再結完全排列組合法 (All Combinations)找出鋁合金板材銲接參數最佳化。研究結果可提供銲接相關業者改善銲接效率。
The welding of aluminum magnesium alloy has superior mechanical characteristics, but the feasible setting for the welding parameters of the TIG (Tungsten Inter Gas Arc Welding) or GTAW (Gas Tungsten Arc Welding) have many difficulties due to some hard and crisp inter-metallic compounds created within the welding line. Normally, the setting of welding parameters does not have a formula to follow; it usually depends on experts' past knowledge and experiences. Once exceeding the rule of thumb, it becomes to be impossible to set up feasibly the optimal parameters. Consequently, this study will develop a solution to solve the problem of multiple quality characteristics when we weld the aluminum magnesium alloy plates. The select welding quality characteristics are non-destructive testing (Welding thickness, Welding width and Depth-width ratio) and destructive testing (Impact Test and Tensile Test). This paper uses TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), ANN (Artificial Neural Network) and all combinations to find the optimal function framework of parameter design for welding of aluminum magnesium alloy. The research results can improve the welding efficiency for relevant welding industries.
期刊論文
1.Chan, Hsiao-ling、Liang, Shing-ko、Lien, Chi-tai(20061100)。A New Method for the Propagation System Evaluation in Wireless Network by Neural Networks and Genetic Algorithm。International Journal of Information Systems for Logistics and Management，2(1)，27-34。new window  new window
2.Juang, S. C.、Tarng, Y. S.(2002)。Process parameter selection for optimizing the weld pool geometry in the tungsten inert gas welding of stainless steel。Journal of Materials Processing Technology，122(1)，33-37。  new window
3.Su, C. T.、Chiu, C. C.、Chang, H. H.(2000)。Optimal parameter design via neural network and genetic algorithm。International Journal of Industrial Engineering，7(3)，224-231。  new window
4.Tong, L. I.、Wang, C. H.(2000)。Optimizing multi-response problems in a dynamic system by grey relational analysis。Journal of the Chinese Institute of Industrial Engineers，17(2)，147-156。  new window
5.Jhang, J. P.、Chan, H. L.(2001)。Application of the Taguchi Method to Improve the Process Yield Rate For Air Cleaners in Toyota Corona Vehicles。International Journal of Reliability, Quality and Safety Engineering，8(3)，219-231。  new window
6.Tong, L.-I.、Su, C.-T.(1997)。Optimizing multi-response problems in the Taguchi method by fuzzy multiple attribute decision making。Quality and Reliability Engineering International，13(1)，25-34。  new window
7.Lin, J. L.、Lin, C. L.(2002)。The use of the orthogonal array with grey relational analysis to optimize the electrical discharge machining process with multiple performance characteristics。International Journal of Machine Tools and Manufacture，42(2)，237-244。  new window
8.Bhattacharya, S.、Pal, K.、Pal, S.(2012)。Multi-sensor based prediction of metal deposition in pulsed gas metal arc welding using various soft computing models。Applied Soft Computing，12(1)，498-505。  new window
9.張旭華(20060700)。Dynamic Multi-Response Experiments by Backpropagation Networks and Desirability Functions。工業工程學刊，23(4)，280-288。new window  new window
10.Chi, S. C.、Hsu, L. C.(2001)。A fuzzy Taguchi experimental method for problems with multi-attribute quality characteristics and its application on plasma arc welding。Journal of the Chinese Institute of Industrial Engineers，18(4)，97-110。  new window
11.Esme, U.、Kazancoglu, Y.、Bayramoglu, M.、Ozgun, S.(2009)。Optimization of weld bead geometry in TIG welding process using grey relation analysis and Taguchi method。Materials and technology，43(3)，143-149。  new window
12.Lin, H.-C.、Su, C.-T.、Wang, C.-C.、Chang, B.-H.、Juang, R.-C.(2012)。Parameter optimization of continuous sputtering process based on Taguchi methods, neural networks, desirability function, and genetic algorithms。Expert Systems with Applications，39(17)，12918-12925。  new window
13.Su, C. T.、Tong, L. I.(1997)。Multi-Response Robust Design by Principal Component Analysis。Total Quality Management，8(6)，409-416。  new window
14.Zhang, H. C.、Huang, S. H.(1995)。Applications of Neural Networks in Manufacturing: A State-of-the-Art Survey。International Journal of Production Research，33(3)，705-782。  new window
15.Rumelhart, David E.、Williams, Ronald J.、Hinton, Geoffrey E.(1986)。Learning Representations by Back-propagating Errors。Nature，323(6088)，533-536。  new window
會議論文
1.Achebo, J. I.(2011)。Optimization of GMAW protocols and parameters for improving weld strength quality applying the Taguchi method。World Congress on Engineerings。London, UK。6-8。  new window
圖書
1.Hwang, C. L.、Yoon, K.(1981)。Multiple Attributes Decision Making Methods and Applications。Berlin。  new window
 
 
 
 
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