Optimizing SUS 304 wire drawing process by grey relational analysis utilizing Taguchi method
来源期刊：International Journal of Minerals Metallurgy and Materials2008年第6期
论文作者：Al-Refaie Abbas
文章页码：714 - 722
摘 要：In the stainless steel 304 （SUS 304） wire drawing process, optimizing the die life and wire tensile strength, which are the larger-the-better quality characteristics （QCH） types, is of main interest. Three control factors, involving reduction ratio, lubricant temperature, and drawing speed, were investigated utilizing L9（34） orthogonal array （OA）. The grey relational analysis was con-ducted for the normalized signal-to-noise （S/N） ratios. The ordinal value of the grey grade was then used to decide optimal factor levels. The anticipated improvements in die life and wire tensile strength were estimated 25.31 h and 22.50 kg/mm2, respectively. To decide the significant factor which had effect on each QCH and predict the average value of each QCH, analysis of variance （ANOVA） was performed for S/N ratio and QCH. Confirmation experiments were then conducted, where a good overlap was noticed between the predicted and confirmation intervals for each QCH. The Hotelling T2 and the sample generalized variance control charts were finally utilized in controlling and monitoring future production. In conclusion, the grey relational analysis utilizing Taguchi method is an effective approach for optimizing the die life and wire tensile strength for SUS wire drawing process.
Al-Refaie Abbas
Department of Industrial Engineering, University of Jordan
摘 要：In the stainless steel 304 （SUS 304） wire drawing process, optimizing the die life and wire tensile strength, which are the larger-the-better quality characteristics （QCH） types, is of main interest. Three control factors, involving reduction ratio, lubricant temperature, and drawing speed, were investigated utilizing L9（34） orthogonal array （OA）. The grey relational analysis was con-ducted for the normalized signal-to-noise （S/N） ratios. The ordinal value of the grey grade was then used to decide optimal factor levels. The anticipated improvements in die life and wire tensile strength were estimated 25.31 h and 22.50 kg/mm2, respectively. To decide the significant factor which had effect on each QCH and predict the average value of each QCH, analysis of variance （ANOVA） was performed for S/N ratio and QCH. Confirmation experiments were then conducted, where a good overlap was noticed between the predicted and confirmation intervals for each QCH. The Hotelling T2 and the sample generalized variance control charts were finally utilized in controlling and monitoring future production. In conclusion, the grey relational analysis utilizing Taguchi method is an effective approach for optimizing the die life and wire tensile strength for SUS wire drawing process.
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