This paper proposes a biomechanical performance design method of joint prosthesis for medical rehabilitation via Generative Structure Optimization (GSO). Firstly, the 3D reconstruction of manifold structure involving hard bone and cartilage is sequentially and progressively implemented from heterogeneous medical images such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) via iteration. On the basis of reconstructed mesh structure, the finite element method (FEM) is hereby employed to verify the structure by evaluating the mechanical force distribution. The biomechanical performance design model for 3 D printing (3DP) is then built using multi-objective optimization (MOO) by considering adaptive layer thickness, infill patterns and infill trajectories, etc. The GSO outlets a generative data-driven system which covers various stages such as personalized CT, subsequent 3 D reconstruction, further finite element analysis (FEA) and even structural parameter optimization. The physical experiment of Additive manufacturing (AM) proves that, the relative density, surface topography and wear-resisting performance of joint prosthesis can be improved by GSO which helps to improve biomechanical performance, including kinematics and dynamics. The proposed method may arouse the huge attention in the prosthesis applications to promote patients’ high-end customization well-being.

This article proposes a support diminution design method for layered manufacturing of manifold surface based on variable orientation tracking (VOT). We aim at reducing the external support or upholders to a minimum with maximum possibility theoretically to save material and diminish material stripping effect (MSE), thereby improving the bilateral surface precision either exterior or interior. The cosmic gravity effect criterion is first used to extract surface need support from manifold surface with various materials by considering the balance force involving material characteristics and inclination angle. In the light of this criterion theory, varying the substrate normal orientation (SNO), namely workbench, for each layer in printing coordinate system, may break the balance between gravity and its equilibrium force. Therefore, the optimal SNO can be rigorously calculated using mathematical harmonic analysis among the continuous domain. To serve for the multidegree of freedom (DOF) on account of SNO, a reconfigurable VOT robot with six-axis DOF is developed for 3D printing (3DP). The matched servo controller is successfully implemented to accurate tracking of both orientation and Cartesian coordinates, using forward kinematic chains as well as reverse kinematic tracking. What is more, the end-effector (extruder) is holding perpendicular to the substrate workbench. The physical experiment that takes human external ear auricle, for example, using a layer-based process is implemented via VOT. The MSE due to supporting material can be clearly observed and diminished using an optical microscope. The stripped material from external support via diminution design can be evaluated quantitatively by electronic weighting balance. All of which indicate the findings that external support in 3DP can be virtually reckoned and diminished using VOT rather than the so-called build orientation traversal method. The VOT method upon which we touched can be widely applied to various layered manufacturing of accurate structure, for instance, cantilever, sandwich, and scaffolds in the occasion needing precise curtailment of outer support multimaterial.