Systematic Literature Review of System Models for Technical System Development

Schmidt, Marvin M.; Zimmermann, Thomas C.; Stark, Rainer

doi:10.3390/app11073014

Cited by 12 publications

(7 citation statements)

References 97 publications

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“…Other databases mentioned in previous reviews [58][59][60] were also used, such as EBSCO Business Source Complete (BSC), IEEE Xplore, Web of Science, Science, and Information Systems Association (AIS). In these databases and in the lists of references (with restriction on the date to 2018-2022), we found 388 more articles in addition to the Scopus database.…”

Section: Methodsmentioning

confidence: 99%

Cross-Industry Principles for Digital Representations of Complex Technical Systems in the Context of the MBSE Approach: A Review

Bolshakov,

Badenko,

Yadykin

et al. 2023

Applied Sciences

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This scientific article discusses the process of digital transformation of enterprises, analyzed as complex technical systems. Digital transformation is essential for businesses to remain competitive in the global marketplace. One of the effective tools for such a transformation is model-based systems engineering (MBSE). However, there is a gap in the practical application of knowledge regarding the uniform principles for the formation of a digital representation of complex technical systems, which limits the realization of the cross-industry potential of digital transformation in the economy. The motivation for this study is to identify common cross-industry principles for the formation of digital representations of complex technical systems that can lead companies to a sustainable and successful digital transformation. The purpose of this work is to identify and formulate these principles through an analysis of publications, using an inductive approach and classifying them by the category of application. As a result of the study, 23 principles were obtained, and the degree of their use in various industries associated with complex technical systems was determined. The results of this study will help to solve the problem of cross-industry integration and guide systemic changes in the organization of enterprises during their digital transformation.

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Section: Methodsmentioning

confidence: 99%

Cross-Industry Principles for Digital Representations of Complex Technical Systems in the Context of the MBSE Approach: A Review

Bolshakov,

Badenko,

Yadykin

et al. 2023

Applied Sciences

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“…Lu [57] surveyed the development trend of MBSE from the perspective of tool-chain development using questionnaires. Schmidt [58] reviewed the literature on a general definition of the term "system model." Henderson [59] empirically analyzed the advantages of MBSE.…”

Section: B Bibliometrics and Mbse Reviewsmentioning

confidence: 99%

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

Wang

et al. 2024

IEEE Trans. Eng. Manage.

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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.

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“…The system model, as a single data source, improves the misunderstandings that natural language may bring to communication between personnel from different domain backgrounds [6]. MBSE has the benefits of improving the quality of engineering projects, improving the consistency and traceability of model design information, as well as the reusability of models and data [7]. MBSE greatly reduces the time cost of project development management [8,9].…”

Section: Introductionmentioning

confidence: 99%

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

Qi,

Luo,

Zhao

et al. 2024

J. Phys.: Conf. Ser.

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The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

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Systematic Literature Review of System Models for Technical System Development

Cited by 12 publications

References 97 publications

Cross-Industry Principles for Digital Representations of Complex Technical Systems in the Context of the MBSE Approach: A Review

Cross-Industry Principles for Digital Representations of Complex Technical Systems in the Context of the MBSE Approach: A Review

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

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

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