標題: Optimisation of the GTA welding process using the Taguchi method and a neural network
作者: Lin, HL
Chou, CP
機械工程學系
Department of Mechanical Engineering
關鍵字: gas tungsten arc welding;neural networks;Taguchi method
公開日期: 1-二月-2006
摘要: There are many parameters that affect gas tungsten arc (GTA) welding process quality. Conventionally, the Taguchi method has been widely used in engineering; however, with this method the desired results can only be obtained with the use of very discrete control factors, thus leading to uncertainty about the real optimum. In this study, the Taguchi method was used for the initial optimisation of the GTA welding process parameters. A neural network was then used to construct the relationships between the welding process parameters and weld pool geometry of each weldment. The optimal parameters of the GTA welding process were determined by simulating significant process parameters obtained by the Taguchi method. Experimental results are provided to illustrate the proposed approach.
URI: http://dx.doi.org/10.1179/174329306X84328
http://hdl.handle.net/11536/12684
ISSN: 1362-1718
DOI: 10.1179/174329306X84328
期刊: SCIENCE AND TECHNOLOGY OF WELDING AND JOINING
Volume: 11
Issue: 1
起始頁: 120
結束頁: 126
顯示於類別:期刊論文