公开(公告)号：US20230315945A1

公开(公告)日：2023-10-05

申请号：US18188331

申请日：2023-03-22

Applicant: DASSAULT SYSTEMES

Inventor： Martin-Pierre SCHMIDT ,  Peter CLAUSEN ,  Claus Bech Wittendorf PEDERSEN ,  Pascal HEBRARD

IPC: G06F30/20 ,  G06F30/10

CPC classification number: G06F30/20 ,  G06F30/10

Abstract: A computer-implemented method for designing a manufacturing product. The method includes obtaining a CAD model representing the manufacturing product. The CAD model includes a feature tree. The feature tree has one or more CAD parameters each having an initial value. The method also includes obtaining an optimization program. The optimization program is specified by one or more use and/or manufacturing performance indicators. The one or more indicators having one or more objective functions and/or one or more constraints. The method further includes modifying the initial values of the one or more CAD parameters by solving the optimization program using a gradient-based optimization method. The optimization method has as free variable the one or more CAD parameters and uses sensitivities. Each sensitivity is an approximation of a respective derivative of a respective performance indicator with respect to a respective CAD parameter.

公开(公告)号：US20230385484A1

公开(公告)日：2023-11-30

申请号：US18324815

申请日：2023-05-26

Applicant: DASSAULT SYSTEMES

Inventor： Peter CLAUSEN ,  Martin-Pierre SCHMIDT ,  Claus Bech Wittendorf PEDERSEN ,  Pascal HEBRARD

IPC: G06F30/23 ,  G06F30/17

CPC classification number: G06F30/23 ,  G06F30/17 ,  G06F2113/24

Abstract: A computer-implemented method for designing a sheet part comprising beads. The method comprises providing a CAD model representing the part. The CAD model includes a feature tree. The feature tree has one or more CAD parameters each having an initial value. The method further comprises providing a bead optimization program specified by one or more use and/or manufacturing performance indicators. The one or more indicators comprise one or more objective function(s) and/or one or more constraints. The method further comprises modifying the initial values of the one or more CAD parameters by solving the optimization program using a gradient-based bead optimization method. The optimization method has as free variables the one or more CAD parameters. The optimization method uses sensitivities. Each sensitivity is an approximation of a respective derivative of a respective performance indicator with respect to a respective CAD parameter.