Multi-Objective Optimization of Dental Implant Designs With Multi-Recessed Holes: Insights From Static and Dynamic Finite Element Analysis.

Abstract

This study presents a novel dental implant design featuring multi-recessed holes, developed through an integrated multi-objective optimization framework. The impact of the implant geometry on longevity, strength, and success rate is explored under both static and dynamic loading conditions. The novel design features multi-recessed holes, and five key implant parameters are selected as control factors for optimization. Experimental simulations are conducted using the uniform design (UD) method. Finite element analysis (FEA) is used to simulate the implant system to evaluate the fatigue safety factor and equivalent stress at the primary, middle, and final stages of osseointegration. Additionally, the dynamic FEA is employed to calculate the maximum micromotion under dynamic chewing loads. To maximize the fatigue safety factor and minimize equivalent stress and micromotion, a multi-objective optimization approach is applied, integrating Kriging interpolation (KGI), entropy weighting analysis (EWA), the technique for order preference by similarity to ideal solution (TOPSIS), and genetic algorithms (GA). The optimal design achieves a fatigue safety factor of 3.022 and an equivalent stress of 459.49 MPa, with improvements of 28.1% and 3.2%, respectively, compared to the original design. Furthermore, the optimized design results in a micromotion of 32.96 μm, reflecting a 37.1% improvement. Overall, the multi-objective optimization process enhances the implant's safety factor and strength under various loading conditions.