Identification of most influential design variables in engineering design optimization

摘要

A method of identifying most influential design variables in a multi-objective engineering design optimization of a product is disclosed. According to one aspect of the present invention, a product is optimized with a set of design variables and a set of response functions as objectives and constraints. Representative product design alternatives (samples) are chosen from the design space and evaluated for responses. Metamodels are then used for fitting the sample responses to facilitate a global sensitivity analysis of all design variables versus the response functions. A graphical presentation tool is configured for allowing the user to conduct "what-if" scenarios by interactively applying respective weight factors to response functions to facilitate identification of most influential design variables. Engineering design optimization is then conducted in a reduced design space defined by the most influential design variables.