| description abstract | In this work, the minimization of warpage was investigated using the “moldflow†software and sequential simplex algorithm based on feedstock properties. Also, the sensitivity analysis was implemented to determine the degree of impact of each parameter on the warpage. This study is divided into two portions: experimental analysis and numerical analysis. First, for the experimental study, four kinds of feedstock with different alumina powder loadings were prepared to investigate the rheological properties. This investigation showed that the feedstock with 60 vol. % alumina powder was the optimum feedstock for the injection molding. Also, the results indicated that the viscosity of feedstock decreases by increasing both the shear rate and temperature. Next, the thermal conductivity of this feedstock was measured at different temperatures and it was found that the change of temperature can greatly influence the thermal conductivity of feedstock. In the numerical study, the injection molding parameters were divided into three categories. Based on the feedstock properties obtained form the first portion, and in order to minimize the warpage, the values of these parameters were sequentially acquired by moldflow and used in the sequential simplex algorithm for gradual convergence to the optimum level. To show the accuracy of numerical results, several samples were injection molded using the injection molding conditions for each vertex; results showed a close correlation between the values obtained by the numerical simulation and by the actual case. After determining the optimum parameter values, the sensitivity analysis was performed to identify the level of influence of each parameter on warpage. The obtained results showed that the most effective parameters on warpage are the mold temperature, packing pressure, and the holding time. Generally, it is demonstrated that the experimental and numerical analysis, performed via the moldflow software and sequential simplex algorithm, together with the sensitivity analysis can be useful in achieving success in the powder injection molding (PIM) technique. | |
