Multidisciplinary design optimization of dental implant based on finite element method and surrogate models

This study aims to propose a Multidisciplinary design optimization (MDO) approach for dental implant based on Finite element method (FEM), surrogate model and a new MDO algorithm. FEM is used to calculate the stress at the implant-bone interface first. Two surrogate models, Support vector regression (SVR) and Kriging (KRG) are built to replace FEM in the following MDO of dental implant, and their verifications indicate their accuracies. A new multidisciplinary design optimization algorithm, named as Homogenization-target-values MDO algorithm (HTV-MDO), is established and first tested by a numerical example to demonstrate its effectiveness. After that, it is applied to the MDO of dental implant based on the SVM and KRG. The results indicate that the new MDO approach proposed in this study can effectively deal with the MDO of dental implant. The stress is reduced greatly with other characteristics of dental implant (contact area and volume of implant in this study) optimizing or slightly deteriorating. This approach can be expanded to other MDO of different bio-implants.