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March 10, 2026Systems Engineering0 citationsOpen Access

Model‐Based Systems Engineering in Space Applications: A Comprehensive Literature Review

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RBRehobot Bekele BurusoSHSara HimmicheTTTaiwo Tejumola

Key Points

  • The aim is to explore current Model-Based Systems Engineering (MBSE) practices and identify effective enablers to improve application strategies.
  • Conducted a comprehensive review of 126 studies published from 2011 to 2023.
  • Analyzed MBSE practices and their enablers through qualitative and quantitative methods.
  • Identified five phases of MBSE relevant to system engineering activities.
  • Revealed four archetypes of MBSE methods tailored to mission complexity.
  • Identified four MBSE languages based on modeling interactions.
  • Categorized seven groups of MBSE tools by their functions and capabilities.
  • Established a strong alignment between MBSE utilization and lifecycle development stages.

Abstract

ABSTRACT The growing complexity of space engineering is driving the demand to embrace the adoption of Model‐Based Systems Engineering (MBSE). Although the MBSE is well‐practiced in the space industry, the level of effort and need required to obtain the benefits of MBSE vastly differ across enterprises; this disparity presents a significant challenge to adopting best practices and establishing a uniform standard procedure. This comprehensive review analyzes 126 studies published between 2011 and 2023 to examine current MBSE practices and their enablers (method, tool, and language) to identify the best strategies of application. This study proposes five phases of MBSE common in all applications: requirements management, model development, simulation and analysis, configuration management, and collaboration and communication, which are core systems engineering activities performed throughout the lifecycle of the system of interest. This review conducts a qualitative and quantitative analysis of MBSE enablers employed across each phase, assessing their frequency of utilization, and functional contributions to SE tasks. The findings reveal four archetypes of the MBSE methods as they evolve to meet different levels of mission complexity and organizational needs, four MBSE languages based on modeling and interactions, and seven groups of MBSE tools categorized by their capabilities and functions. The utilization of MBSE enablers across MBSE phases demonstrated a strong alignment with the development of lifecycle stages, providing better guidance for the practical implementation. Finally, the study identifies key opportunities and challenges for future research to advance MBSE practice further.

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Cite This Study

Buruso et al. (2026) studied this question.

synapsesocial.com/papers/69af958570916d39fea4d258https://doi.org/10.1002/sys.70051
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