Combining Taguchi Signal-to-noise Ratio and Grey Relational Analysis into a Multi-objective Optimal Model for Milling Inconel 718 Superalloy

結合田口法訊噪比與灰關聯分析建構Inconel 718超合金銑削加工多目標參數最佳化模式

江新祿(Hsiu-Lu Chiang) ； 楊慶彬(Ching-Been Yang) ； 許春耀(Chun-Yao Hsu)

《中國機械工程學刊》 37卷6期 (2016/12) Pp. 625-633

摘要

This study explored how varied factors (cutting tools, cutting speeds, cutting depths, ultrasonic vibrations and coolants) would work on the milling of Inconel 718 super alloy, in order to bring out the best cutting results. The experiments showed that the use of HC 844 ISO P20-P30 cutting tools can effectively reduce surface roughness and prolong the life of the cutting tools (less flank wear), if run at the lower cutting and feeding speeds for less cutting depth. The reduced surface roughness and flank wear of the cutting tools are two major objectives for which the Inconel 718 super alloy was designed. In this report, a method was proposed of converting Taguchi's signal-to-noise (S/N) ratio into grey relational coefficients and degrees and combining them with grey relational analysis , which would result in optimal complementary parameters to resolve the mutual conflicts of the factors involved. According to the experiments, when the flank wear was the single objective in Taguchi analysis, the average flank wear and surface roughness were respectively 0.174mm and 0.468f,!m, indicating that the achievement of the least flank wear would cause slightly greater Surface roughness; and vice versa (when the surface roughness is the single objective in Taguchi analysis, the average flank wear and surface roughness are respectively 0.262mm and 0.203μm). Using grey relational factors to analyze the optimal complementary parameters of multiple quality factors, the average flank wear and surface roughness are 0.192mm and 0.235μm, hence having solved the conflicts of multifactor quality requirements in Taguchi analysis.

關鍵字

Inconel 718 ； tool wear ； Taguchi method ； grey relational analysis ； multi-objective

並列摘要

工件之表面粗糙度小及刀具壽命長(刀腹磨耗少)為Inconel 718超合金銑削加工追求之双目標。本文提出之結合灰關聯分析與田口S/N ratio的方法，將田口法求得的S/N ratio轉換成灰關聯係數及灰關聯度，可求得多目標品質之最佳參數組合，並解決田口法分析之因子水準在多重目標品質要求下所產生之相互衝突。由驗證實驗顯示，以田口分析刀腹磨耗為單一目標下，最佳參數組合之刀腹磨耗平均值為0.174 mm，表面粗糙度平均值為0.468μm，此代表在追求最佳之刀腹磨耗為單一目標品質時，就會稍微犧牲另一目標表面粗糙度之品質。而以田口分析表面粗糙度為單一品質之最佳參數組合之刀腹磨耗平均值為0.262mm，表面粗糙度平均值為0.203μm，代表在追求最佳之表面粗糙度為單一目標品質時，就會稍微犧牲另一目標刀腹磨耗之品質。而以灰關聯分析刀腹磨耗與表面粗糙度為雙品質目標之最佳參數組合之刀腹磨耗平均值為0.192mm，表面粗糙度平均值為0.235μm，較前兩組更能同時兼顧刀腹磨耗與表面粗糙度之品質。由驗證實驗顯示，結合灰關聯分析可解決田口法分析之因子水準在多重目標品質要求下所產生之相互衝突。