Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2026
Surface roughness optimisation in FFF tibial insert patterns for silicone mould.
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Sharma Raman, Kumar Narendra, Trehan Rajeev
Аннотация
Most commercially available knee implant components are confined to standardised size ranges, hindering precise anatomical alignment and proper gap filling. This study focuses on producing silicone moulds for patient-specific knee implants using an indirect rapid tooling process. Total knee replacement (TKR) components were generated from CT scan data via image segmentation, CAD modelling, STL correction and resection planning. The profile for the tibial insert was extracted from the CAD models of femoral and tibial components of TKR. Further, the profile as obtained was employed to fabricate a pattern of the tibial insert by Fused Filament Fabrication (FFF) using PLA filaments. Two post-processing techniques, chemical immersion and chemical vapour smoothing, were used and compared to improve the surface finish. The more effective chemical vapour smoothing method was applied to the pattern. The effects on surface quality were assessed using an optical tilt microscope. The 3D surface plots confirmed that the post-processing improved the surface finish of the patterns by about 80%. Evaluation of geometric deviation confirmed that chemical vapour smoothing uniformly modifies the entire surface while maintaining global geometric conformity. The result encouraged us to fabricate the silicone moulds, which can further be used to produce patient-specific tibial inserts by casting viable epoxy-based composite biomaterials. FFF-fabricated tibial insert moulds showed Ra 26.87 µm, Rq 33.58 µm, Rsk -1.19, and Rku 3.12. Rapid tooling with an unsmoothed pattern increased roughness (Ra 54.60 µm, Rq 57.31 µm) and altered height distribution (Rsk 0.31, Rku 2.40). Vapour smoothing prior to moulding significantly reduced Rq and stabilised Rsk and Rku, indicating improved surface morphology and uniform asperity distribution.