Modeling and Understanding Large Scale Complex Systems

2025-01-0443

09/16/2025

Authors Abstract
Content
The objective of this paper is two-fold. Firstly, provide guidance to best implement end to end traceability from program requirements to physical implementation, and Secondly provide techniques to review and understand large scale complex systems. Even with a Digital Engineering Environment (DEE) being an enabler towards applying Systems Engineering practices to develop large scale complex systems, many organizations are unclear on the methodology for modeling their architectures and enabling stakeholders to easily review, understand and assess those architectures. An architecture can be a conceptual, logical or physical architecture, depending on the system’s lifecycle state. For the context of this paper, the modeling environment is any System’s Modeling Language (SysML) based tool along with modeling tools for electrical, mechanical and software development and product life cycle management tool. The intended audience is any engineering organization defining end-to-end architecture within a DEE, and all stakeholders tasked with reviewing conceptual, logical and physical architecture. The outcome of this paper is to provide engineering organizations with guidance on underlying principles for modeling and understanding or assessing architecture that describe large complex systems.
Meta TagsDetails
DOI
https://doi.org/10.4271/2025-01-0443
Pages
22
Citation
Khaled-Noveloso, L., "Modeling and Understanding Large Scale Complex Systems," SAE Technical Paper 2025-01-0443, 2025, https://doi.org/10.4271/2025-01-0443.
Additional Details
Publisher
Published
Sep 16
Product Code
2025-01-0443
Content Type
Technical Paper
Language
English