Optimization Workflows for Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO)

Abstract

Developing modern products involves numerous domains (controlling, production, engineering, etc.) and disciplines (mechanics, electronics, software, etc.). The products have become increasingly complex while their time to market has decreased. These challenges can be overcome by Model-Based Systems Engineering (MBSE), where all development data (requirements, architecture, etc.) is stored and linked in a system model. In an MBSE system model, product requirements at the system level can lead to numerous technical variants with conflicting objectives at the parameter level. To determine the best technical variants or tradeoffs, Multidisciplinary Analysis and Optimization (MDAO) is already being used today. Linking MBSE and MDAO allows for mutually beneficial synergies to be expected that have not yet been fully exploited. In this paper, a new approach to link MBSE and MDAO is proposed. The novelty compared to existing approaches is the reuse of existing MBSE system model data. Models developed during upstream design and test activities already linked to the MBSE system model were integrated into an MDAO problem. Benefits are reduced initial and reconfiguration efforts and the resolution of the MDAO black-box behavior. For the first time, the MDAO problem was modeled as a workflow using activity diagrams in the MBSE system model. For a given system architecture, this workflow finds the design variable values that allow for the best tradeoff of objectives. The structure and behavior of the workflow were formally described in the MBSE system model with SysML. The presented approach for linking MBSE and MDAO is demonstrated using an example of an electric coolant pump.