Optimum Material Gradient for Functionally Graded Dental Implant Using Particle Swarm Optimization

One of the main issues facing dental implantation, which makes osseointegration and bone remodeling problematical, is a mismatch of mechanical properties between engineered and native biomaterials. Functionally Graded Materials (FGMs) has been proposed as a potential alternative to some conventional implant materials such as titanium for selection in prosthetic dentistry. The idea of FGM dental implant is that the property would vary in a certain pattern to match the biomechanical characteristics required at different regions in the hosting bone. This research presents some important findings for the FGM dental implant design in optimization of material gradient. Due to the nature of the problem, multi-objective optimization methods should apply for solving multi-criteria problems. The Pareto front was determined using the Multi-Objective Particle Swarm Optimization (MOPSO). The obtained results from the MOPSO confirm the results obtained by the Response Surface Methodology (RSM) in addition to offering further improvements.