Comparative Analysis of an MBSE Approach to a Traditional SE Approach for Architecting a Robotic Space System through Knowledge Categorization

This study seeks to compare the types and quantities of knowledge that are captured by model-based systems engineering (MBSE) and traditional architecting approaches to measure the benefits of MBSE in managing the complexity of robotic space systems. An MBSE approach was applied to architecting an orbiting sample Capture and Orient Module (COM) system concept for a Capture, Contain, and Return System (CCRS) payload concept for potential Mars Sample Return (MSR). An architecture framework was established, covering the system, subsystem, and assembly levels of the system, along with structural, behavioral, data, and requirements perspectives. The COM system architecture was captured in parallel using both MBSE and non-MBSE approaches in order to provide a side-by-side comparison of approaches. The approaches were evaluated based on how well each represented the information content of the COM system architecture. A total of 4,389 knowledge elements were classified using the Revised Bloom’s Taxonomy knowledge dimension and used to quantitatively compare the two approaches. The MBSE approach was measured to more completely capture architectural knowledge than the non-MBSE, document-based approach. Limitations to the MBSE approach were also identified, including its ability to fully represent certain high-level conceptual, procedural, and metacognitive knowledge such as design principles, design approaches and rationales, risks, development strategies and rationales, organizational core competencies, and requirement verification methods. The overall results help demonstrate the benefits of MBSE in managing the complexity of robotic space systems and strengthen the case for adopting MBSE within the broader systems engineering community.