Robustimizer: A graphical user interface application for efficient uncertainty quantification, robust optimization, and reliability-based optimization of processes and designs

Abstract

The primary goal of this work is to provide easy-to-use and cutting-edge optimization software designed to handle uncertainties, intended for use in research and education. Robustimizer offers efficient uncertainty quantification through exact analytic formulas using specific surrogate models, such as Gaussian Processes. Moreover, it supports integration with other software packages, and automatic updating of initial design space through exploration–exploitation techniques, among other features. This software has proven its value in sustainable manufacturing, where optimizing processes to reduce environmental impact while managing uncertainties is critical. In this article, the Robustimizer graphical user interface is introduced as a domain-independent optimization tool for surrogate-model-based robust and reliability-based design or process optimization.