Multiple Performance Optimization for the Best Injection Molding Process of Ti-6Al-4V Green Compact

Abstract

The L27 (313) Taguchi orthogonal array is used in the experiment while the injection pressure, injection temperature, powder loading, mold temperature, holding pressure and injection speed are optimized in this study. A grey relational grade (GRG) obtained from the grey relational analysis (GRA) is used to solve the titanium alloy powder injection molding operations with the multiple performance characteristics such as strength and density. From the analysis of variance (ANOVA), the injection temperature has the highest contribution at confidence level 90% to the quality of green part followed by powder loading. The others factor such as mold temperature, holding pressure, injection pressure and injection rate and all the interactions are not significant even though it give contribution during injection molding but the confidence level are less than 90%.

Optimization of Injection Molding Parameters for HDPE/TiO2 Nanocomposites Fabrication with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis

“…More specifically, an orthogonal array denoted by $O{A}_N\left(s^m\right)$ is an $N\times m$ matrix with ‘ N ’ rows and ‘m’ columns, with ‘s’ being the elements of the system [45]. The unique characteristic of such an array is that any particular ordered pair of elements appears the same number of times in all of the columns.…”

“…Complementing the grey relational analysis is the Taguchi method that attempts to calculate the signal-to-noise (S/N) ratios of the different attributes for the optimization of the process by improving the desired characteristics, while reducing the effect of noise and defects at the same time [ 16 , 43 ]; moreover, Taguchi orthogonal arrays [ 44 ] provide a mechanism for the design of experiments based on the number of factors and control levels. More specifically, an orthogonal array denoted by is an matrix with ‘ N ’ rows and ‘m’ columns, with ‘s’ being the elements of the system [ 45 ]. The unique characteristic of such an array is that any particular ordered pair of elements appears the same number of times in all of the columns.…”

“…The unique characteristic of such an array is that any particular ordered pair of elements appears the same number of times in all of the columns. The most commonly-used arrays are L 8 , L 9 , L 16 and, sometimes, L 32 [ 45 ]. Grey relational analysis combined with Taguchi arrays has been used to optimize many injection molded parameters, the results of which varied by different starting materials [ 16 , 23 , 25 , 31 , 46 , 47 , 48 , 49 ].…”

“…In a study by Yang [ 24 ], Young’s modulus, ultimate stress and strain variation were the performance attributes, and it was concluded that melt temperature had the most prominent effect on the mechanical properties of the polycarbonate composites reinforced with glass fiber and PTFE. Moreover, Muhammad et al [ 45 ] employed the grey relational analysis along with an L 27 Taguchi orthogonal array to optimize injection molding parameters to produce Ti-6Al-4V composites. At 90% confidence level, from ANOVA, the injection temperature was found to have the most significant effect on the performance characteristics, such as strength and density [ 45 ].…”

“…Moreover, Muhammad et al [ 45 ] employed the grey relational analysis along with an L 27 Taguchi orthogonal array to optimize injection molding parameters to produce Ti-6Al-4V composites. At 90% confidence level, from ANOVA, the injection temperature was found to have the most significant effect on the performance characteristics, such as strength and density [ 45 ]. Furthermore, in optimizing the turning operation parameters for the SKD 11 alloy, Tzeng et al [ 32 ] concluded that the depth of cut was the most important factor affecting the roughness and roundness of the material.…”