Research is proposed to develop a novel Automated System Architecture Generation (ASAG) tool that automates the development of a system architecture model, in SysML format, from disparate sources, integrates SysML models together, and identifies the impacts of a baseline change across the models. A multilayer, time independent machine learning model will be used to automate the capture of dissimilarly-formatted source data and fill in missing data to ensure a SysML-compliant model after all sources are integrated. Approved for Public Release | 21-MDA-11013 (19 Nov 21)
