Abstract. This paper introduces the application of uniform experimental design to improve dental implant systems subjected to dynamic loads. The dynamic micromotion of the Zimmer dental implant system is calculated and illustrated by explicit dynamic finite element analysis. Endogenous and exogenous factors influence the success rate of dental implant systems. Endogenous factors include: bone density, cortical bone thickness and osseointegration. Exogenous factors include: thread pitch, thread depth, diameter of implant neck and body size. A dental implant system with a crest module was selected to simulate micromotion distribution and stress behavior under dynamic loads using conventional and proposed methods. Finally, the design which caused minimum micromotion was chosen as the optimal design model. The micromotion of the improved model is 36.42 Pm, with an improvement is 15.34% as compared to the original model.
Abstract:This study aimed to analysis the micromotion of the3i, Branemark and Semados dental implant systems with Zimmer implant model subjected to dynamic chewing loads. Micromotion of the three dental implant systems with basic dimensions was obtained using dynamic finite element analysis. From the results, the best abutment type had been selected. Six parameters of the implant were selected as the control factors to be improved. A uniform design method was employed to construct a set of experimental simulations. Next, for each experimental simulation, the dynamic finite element analysis package ANSYS/LS-DYNA was employed to simulate the behavior of the Zimmer dental implant model subjected to dynamic chewing loads and then determined the maximum micromotion of the cortical and cancellous bones. Finally, the best design of the experimental simulations that caused the smallest amount of micromotion was selected as the improved design version. Compared to the original design, which experienced micromotion of 33.39 m, the improved version experienced micromotion of 22.22 m. The rate of improvement was 33.45 %.Finally, the micromotion predicted system in commercial and engineering applications is constructed by Kriging interpolation method.
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