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An axiomatic system engineering design method based on NSGA-II algorithm applied to complex systems.

Xiaoqian Zhang1, Qinghai Zhang2, Qingjian Zhao2

  • 1Shandong Key Laboratory of Space Debris Monitoring and Low-orbit Satellite Networking, Qingdao University of Technology, Qingdao, 266525, Shandong, China. zhangxiaoqian@stu.qut.edu.cn.

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Summary
This summary is machine-generated.

This study introduces an integrated framework combining Axiomatic Design and Model-Based Systems Engineering with NSGA-II optimization for complex system design. It enhances modularity analysis and coupling identification, reducing expert dependency.

Keywords:
Active Reflective Surface Control SystemAxiomatic designModel-Based Systems EngineeringNSGA-IISystem design methodology

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Area of Science:

  • Systems Engineering
  • Computational Engineering
  • Design Science

Background:

  • Complex systems engineering requires robust methods for managing interdependencies.
  • Traditional approaches often rely heavily on expert knowledge for design structure optimization.
  • Integrating formal design principles with advanced optimization is crucial for enhancing system modularity.

Purpose of the Study:

  • To propose an integrated framework combining Axiomatic Design, Model-Based Systems Engineering (MBSE), and NSGA-II for complex system design.
  • To develop a multi-level traceability matrix for linking system elements from requirements to physical structure.
  • To enhance the analysis of coupling relationships and support modularity-oriented design through intelligent optimization.

Main Methods:

  • Development of an integrated framework using SysML for formal mappings across user, functional, behavioral, and physical domains.
  • Construction of a multi-level traceability matrix to ensure bidirectional traceability.
  • Incorporation of the NSGA-II algorithm to dynamically optimize the Design Structure Matrix (DSM) sequencing and quantitatively assess coupling degrees based on Axiomatic Design principles.

Main Results:

  • The framework establishes formal mappings and ensures bidirectional traceability between system domains.
  • NSGA-II dynamically optimizes DSM sequencing, enhancing visualization and explicitness of coupling relationships.
  • A case study on an active reflector control system demonstrated significant reduction in reliance on expert knowledge for DSM ordering.

Conclusions:

  • The proposed NSGA-II-enhanced framework offers a systematic approach to modularity analysis in complex systems.
  • It provides clear advantages in coupling identification and modularity assessment compared to traditional methods.
  • The framework effectively accelerates convergence in large-scale design spaces, improving design process efficiency.