Nanopowders provide better details for micro features and surface finish in powder injection molding processes. However, the small size of such powders induces processing challenges, such as low solid loading, high feedstock viscosity, difficulty in debinding, and distinctive sintering behavior. Therefore, the optimization of process conditions for nanopowder injection molding is essential, and it should be carefully performed. In this study, the powder injection molding process for Fe nanopowder has been optimized. The feedstock has been formulated using commercially available Fe nanopowder and a wax-based binder system. The optimal solid loading has been determined from the critical solid loading, measured by a torque rheometer. The homogeneously mixed feedstock is injected as a cylindrical green body, and solvent and thermal debinding conditions are determined by observing the weight change of the sample. The influence of the sintering temperature and holding time on the density has also been investigated. Thereafter, the Vickers hardness and grain size of the sintered samples have been measured to optimize the sintering conditions.
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Powder injection molding is an important manufacturing technology to mass produce superalloy components with complex shape. Injection molding step is particularly important for realizing a desired shape, which requires much time and efforts finding the optimum process condition. Therefore computer aided engineering can be very useful to find proper injection molding conditions. In this study, we have conducted a finite element method based simulation for the spiral mold test of superalloy feedstock and compared the results with experimental ones. Sensitivity analysis with both of simulation and experiment reveals that the melt temperature of superalloy feedstock is the most important factor for the full filling of mold cavity. The FEM based simulation matches well the experimental results. This study contributes to the optimization of superalloy powder injection molding process.
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