A Bibliometric Analysis on Model-based Systems Engineering

Jinzhi Lu
IEEE, 2021
Article de conférence

Model-based systems engineering (MBSE) has been accepted as an extremely important approach to understanding the multi-domain research field comprehensively. In this paper, a bibliometric analysis is used to conduct a comprehensive survey of model-based systems engineering literature of the last five years. The VOSViewer is used to implement visual network analysis for co-authorship, citation, and co-occurrence of the MBSE related papers. The results of the bibliometric study, firstly, reveal the influential research teams and sources. Secondly, research hotspots in the current MBSE domain are identified. The findings of this study aim to help researchers to gain a faster and deeper understanding of the current literature on MBSE.

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Jinzhi Lu
IEEE, 2021
Article de conférence

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https://infoscience.epfl.ch/record/296883?ln=fr

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Bibliometric Analysis of Model-Based Systems Engineering: Past, Current, and Future

Jinzhi Lu, Yan Yan

Model-based systems engineering (MBSE) is considered an important approach for understanding multidomain fields and is widely used in complex systems such as aerospace. In this article, a detailed survey of MBSE literature was conducted from its commencement to the present trends through bibliometric analysis. Some bibliometric tools were used to implement a visual network analysis of MBSE-related manuscripts. The results of the bibliometric study revealed the interrelationship and distribution of researchers in multidomain fields. The authorized sources of MBSE papers were also assorted. The current practices of MBSE were analyzed. The future directions for MBSE based on the current practices were discussed. We found that MBSE's research has been conducted by many research teams with distinctive characteristics, and the top publishing sources in this field have emerged. Research on MBSE focuses on system engineering, languages, system of systems, and digitalization. The development of new technologies such as next-generation modeling languages is improving current practical problems. The findings of this study may help researchers gain a faster and more comprehensive understanding of the current and future developments in MBSE.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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