ROBUSTNESS IMPROVEMENT USING OPEN SOURCE CODE LIBRARIES

Abstract

Computer tools are commonly used to assess designs. We develop a toolchain using open source code libraries in Python to provide an open source, interactive robust design improvement toolchain. A reference folder contains a script that reads an input parameter value file and runs the simulation. The toolchain executes uncertainty quantification steps by replicating the reference folder. This is repeated for design points, and mean and sigma graphs generated versus each design variable. This fits within a workflow of defining variation modes, design variables, and toolchain execution.