Aluminum metal composites primed by fused deposition modeling-assisted investment casting: Hardness,surface,wear,and dimensional properties

Abstract

Fused deposition modeling -based three-dimensional printing techniques, when merged with the investment casting process, is one of the most innovative techniques for developing functionally graded metal–matrix composites in high-performance industrial applications. In this study, Al–Al₂O₃ matrix composites have been prepared by the combined route of fused deposition modeling and modified investment casting processes. In the first step, the Al–Al₂O₃ particles have been reinforced into nylon 6 thermoplastics for the preparation of fused deposition modeling-based feedstock filaments (in two configurations: C1 (60% nylon 6–30% Al–10% Al₂O₃) and C2 (60% nylon 6–28% Al–12% Al₂O₃). In the next step, the investment casting patterns of the fused deposition modeling process of nylon 6–Al–Al₂O₃ composites were prepared. Furthermore, the investment casting has been performed by controlling the proportion of nylon 6–Al–Al₂O₃, the volume of pattern, the density of pattern, barrel finishing media weight, barrel fining time, and number of mold wall layers considering Taguchi L₁₈-based experimental design. Finally, the functional aluminum matrix composites were subjected to testing to investigate average surface roughness (R_a), deviation inside the cube, average wear, and average hardness. The study results have suggested that maintaining a higher proportion of Al₂O₃ in three-dimensional printed parts leads to higher R_a, higher dimensional deviation, and higher hardness of investment cast parts. On the contrary, solid patterns have provided low wear rates and low-density patterns resulting in increased wear rates in final investment casted products. Furthermore, the responses are optimized concurrently with the “technique for order of preference by similarity to ideal solution–Taguchi” technique while considering the analytical hierarchical process and entropy weights of significance.