Design optimization using Statistical Confidence Boundaries of response surfaces: Application to robust design of a biomedical implant

Laetitia Rossi (1) , Jean-Marc Linares (2) , Julien Chaves-Jacob (1) , Jean Mailhé (1) , Jean-Michel Sprauel (1)

1 AMU - Aix Marseille Université
2 ISM - Institut des Sciences du Mouvement Etienne Jules Marey

This paper deals with the use of Statistical Confidence Boundaries (SCB) of response surfaces in robust design optimization. An empirical model is therefore selected to describe a real design constraint function. This constraint is thus approximated by a second order polynomial expansion which is fitted to numerical simulations that use a Finite Element Method (FEM). A technique is also proposed to analyze the effects of the uncertainties of the inputs of the simulations. This approach is employed to optimize the design of a biomedical wrist implant. A real optimized implant is then manufactured and tested to validate the numerical model.

Domaines: Mécanique des solides [physics.class-ph]; Biomécanique [physics.med-ph]

Laetitia Rossi, Jean-Marc Linares, Julien Chaves-Jacob, Jean Mailhé, Jean-Michel Sprauel. Design optimization using Statistical Confidence Boundaries of response surfaces: Application to robust design of a biomedical implant. CIRP Annals - Manufacturing Technology, 2014, 63 (1), pp.141--144. ⟨hal-01303708⟩