期刊文献+

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron 被引量:4

原文传递
导出
摘要 High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (Fr) and surface roughness (Ra) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on Fr and Ra were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize Fr and Ra. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to respo ses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100m/min, 0.05mm/r, and 0.1mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (SIN) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.
出处 《Advances in Manufacturing》 SCIE CAS CSCD 2018年第4期419-429,共11页 先进制造进展(英文版)
  • 相关文献

参考文献1

共引文献3

同被引文献17

引证文献4

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部