Novel Methodology for Obtaining Design Structure Matrices Using Network Identification

ABSTRACT Design structure matrices (DSMs) are used to comprehensively represent complex systems. They visualize and describe the dependencies between various variables, processes, states, and events. As such they are used in several system engineering approaches, such as requirement and interface management, fault detection, and supervisory control. Currently, a DSM is typically built from knowledge of experts. This may lead to an incomplete or imbalanced DSMs. For instance, elements and links might be missing or superfluous. In this article, we propose a novel method to acquire the DSM using state‐of‐the‐art network identification methods. This demonstrates a proof‐of‐principle of identifying DSMs from data as an additional tool to the standard heuristic approach. In the future, we plan to embed DSMs in system design and supervisory controllers. We apply this technique to identify the DSM of a fusion reactor modeled by a five‐chamber plasma model describing the transport in a tokamak.

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Publication Details

Journal
Systems Engineering
Published
2026-10-30
DOI
https://doi.org/10.1002/sys.70097
Primary Topic
Systems Engineering Methodologies and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Novel Methodology for Obtaining Design Structure Matrices Using Network Identification

E. M. M. Kivits, M. van Berkel, Marco De Baar, P. Figueiredo
Systems Engineering
Systems Engineering Methodologies and Applications
article

Novel Methodology for Obtaining Design Structure Matrices Using Network Identification

E. M. M. Kivits, M. van Berkel, Marco De Baar, P. Figueiredo
article en

Abstract

ABSTRACT Design structure matrices (DSMs) are used to comprehensively represent complex systems. They visualize and describe the dependencies between various variables, processes, states, and events. As such they are used in several system engineering approaches, such as requirement and interface management, fault detection, and supervisory control. Currently, a DSM is typically built from knowledge of experts. This may lead to an incomplete or imbalanced DSMs. For instance, elements and links might be missing or superfluous. In this article, we propose a novel method to acquire the DSM using state‐of‐the‐art network identification methods. This demonstrates a proof‐of‐principle of identifying DSMs from data as an additional tool to the standard heuristic approach. In the future, we plan to embed DSMs in system design and supervisory controllers. We apply this technique to identify the DSM of a fusion reactor modeled by a five‐chamber plasma model describing the transport in a tokamak.

Systems Engineering
Dutch Institute for Fundamental Energy Research (NL), Eindhoven University of Technology (NL)
UK Atomic Energy Authority, EUROfusion, European Commission, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Euratom Research and Training Programme
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Systems Engineering Methodologies and Applications
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