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Decision Making with Model-Based Systems Engineering
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Decision Making with Model-Based Systems Engineering

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Engineering".

Deadline for manuscript submissions: closed (20 June 2024) | Viewed by 16173

Special Issue Editors

Prof. Dr. Gregory S. Parnell

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Interests: systems engineering; decision analysis; risk analysis; agile systems design; project management
Special Issues, Collections and Topics in MDPI journals
Dr. Eric Specking

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Interests: systems engineering; decision quality; engineering and project management; engineering educationsystems engineering; decision quality; engineering and project management; engineering education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Model-based systems engineering (MBSE) is an approach to systems engineering that emphasizes the use of models to facilitate system design, analysis, and decision making throughout a system's life cycle. Decision making is a critical aspect of MBSE, as it enables engineers to make informed choices based on the models that they have created.

The role of decision making in MBSE is to use models to evaluate different alternatives and select the best course of action. MBSE models can represent a wide range of system elements, including system requirements, functions, behavior, and performance. By modeling and simulating a system's behavior and performance under different conditions, engineers can use MBSE to evaluate trade-offs and make decisions concerning the best design choices.

The models used in MBSE also enable engineers to explore “what-if” scenarios, allowing them to model, simulate, and evaluate different options without committing to a particular design. This helps to reduce risk and uncertainty in the decision-making process, as engineers can test the implications of their decisions before implementing them.

In summary, decision making is a critical aspect of MBSE, as it enables engineers to make informed choices based on models that represent various aspects of a system. MBSE models facilitate decision making by simulating system behavior and performance, evaluating trade-offs, and exploring different options.

Prof. Dr. Gregory S. Parnell
Dr. Eric Specking
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • decision making with MBSE
  • decision analysis with MBSE
  • systems analysis with MBSE

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Published Papers (6 papers)

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Research

25 pages, 8860 KiB  
Article
Architecture Design Space Generation via Decision Pattern-Guided Department of Defense Architecture Framework Modeling
by Zhemei Fang, Xuemeng Zhao and Fengyun Li
Systems 2024, 12(9), 336; https://doi.org/10.3390/systems12090336 - 31 Aug 2024
Cited by 1 | Viewed by 2045
Abstract
The importance of architecture design keeps increasing as the complexity of systems and system-of-systems (SoSs) continues rising. While the architecture frameworks such as the Department of Defense Architecture Framework (DoDAF) are commonly used to guide architecture design, many perspectives are still hindering their [...] Read more.
The importance of architecture design keeps increasing as the complexity of systems and system-of-systems (SoSs) continues rising. While the architecture frameworks such as the Department of Defense Architecture Framework (DoDAF) are commonly used to guide architecture design, many perspectives are still hindering their effective use. Instead of generating a set of architecture description models probably only for satisfying the milestone review, the architecture frameworks should be used to organize the vague or incomplete information, identify and formulate the decision-making problem, and guide the architecture decision-making. Unfortunately, the decision points are hidden in the architecture models and the ambiguity often leads to a confusion of whether the architecture models are built incorrectly due to the lack of modeling experience or the lack of adequate decision analysis. Therefore, this paper identifies the key decision points and decision types during the architecture model development based on the DoDAF. Plus, this paper proposes a set of decision patterns and a guide to their use to provide qualitative decision analysis for developing architecture models and generating alternatives. An illustrative example to anti-submarine SoSs demonstrates the process of applying the decision patterns to the DoDAF model’s development and the generated architecture alternatives. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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15 pages, 3662 KiB  
Article
Applying MBSE to Optimize Satellite and Payload Interfaces in Early Mission Phases
by Shayna Slobin, Zizung Yoon and Susanne Fugger
Systems 2024, 12(8), 310; https://doi.org/10.3390/systems12080310 - 19 Aug 2024
Viewed by 1738
Abstract
The use of model-based systems engineering (MBSE) has been increasingly explored recently in industries that require multi-discipline engineering coordination. In the European space industry, applying MBSE for the engineering of space systems has been an ongoing undertaking on many missions. In the following [...] Read more.
The use of model-based systems engineering (MBSE) has been increasingly explored recently in industries that require multi-discipline engineering coordination. In the European space industry, applying MBSE for the engineering of space systems has been an ongoing undertaking on many missions. In the following paper, the MBSE activities in CAMEO conducted during the A/B1 phases of a typical Earth observation satellite engineered by Airbus are discussed in detail in the form of a case study. The analyses shown are based around the modeling of the spacecraft electrical interfaces in CAMEO. This model was used to automate electrical interface control documents (EICDs) and enable the control of electrical interface development. These methodologies were further put in the context of Airbus’ satellite design processes to assess the benefits of an MBSE approach to the current electrical interface engineering procedure and the potential for the reuse of CAMEO models between satellite projects. The reduction in system engineering effort through the reuse of models to modularly create similar satellite systems for efficient concept evaluation and comparison is a clear benefit. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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37 pages, 5239 KiB  
Article
A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production
by Svetlana Lawrence and Daniel R. Herber
Systems 2024, 12(8), 290; https://doi.org/10.3390/systems12080290 - 8 Aug 2024
Cited by 2 | Viewed by 2098
Abstract
A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers [...] Read more.
A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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28 pages, 6189 KiB  
Article
Cyber Evaluation and Management Toolkit (CEMT): Face Validity of Model-Based Cybersecurity Decision Making
by Stuart Fowler, Keith Joiner and Siqi Ma
Systems 2024, 12(7), 238; https://doi.org/10.3390/systems12070238 - 1 Jul 2024
Viewed by 1926
Abstract
The Cyber Evaluation and Management Toolkit (CEMT) is an open-source university research-based plugin for commercial digital model-based systems engineering tools that streamlines conducting cybersecurity risk evaluations for complex cyber-physical systems. The authors developed this research tool to assist the Australian Defence Force (ADF) [...] Read more.
The Cyber Evaluation and Management Toolkit (CEMT) is an open-source university research-based plugin for commercial digital model-based systems engineering tools that streamlines conducting cybersecurity risk evaluations for complex cyber-physical systems. The authors developed this research tool to assist the Australian Defence Force (ADF) with the cybersecurity evaluation of complicated systems operating in an increasingly contested and complex cyber environment. This paper briefly outlines the functionality of the CEMT including the inputs, methodology, and outputs required to apply the toolkit using a sample model of the process applied to a generic insider threat attack. A face validity trial was conducted on the CEMT, surveying subject-matter experts in the field of complex cybersecurity analysis and risk assessment to present the generic case study and gather data on the expected benefits of a real-world implementation of the process. The results of the face validity broadly supports the effectiveness and usability of the CEMT, providing justification for industry research trials of the CEMT. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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18 pages, 4119 KiB  
Article
Concurrent Value-Driven Decision-Making Process for the Aircraft, Supply Chain and Manufacturing Systems Design
by Giuseppa Donelli, Luca Boggero and Björn Nagel
Systems 2023, 11(12), 578; https://doi.org/10.3390/systems11120578 - 18 Dec 2023
Cited by 4 | Viewed by 2588
Abstract
The integration of product design and supply-chain management can lead to an increase in the profitability and efficiency of companies. However, considering manufacturing, supply chain, and aircraft criteria in the early design phase increases the size of the solutions’ trade space and, thus, [...] Read more.
The integration of product design and supply-chain management can lead to an increase in the profitability and efficiency of companies. However, considering manufacturing, supply chain, and aircraft criteria in the early design phase increases the size of the solutions’ trade space and, thus, the complexity of performing the decision-making process. This paper demonstrates how to leverage value-model theory to simplify the decision-making process when multiple criteria related to multiple systems are considered at the same time. The proposed concurrent approach is formalized from a systems-engineering perspective, considering the interactions between the lifecycle stages of the System of Interest, i.e., the aircraft, and Enabling Systems like the supply chain and manufacturing. A value-based interactive dashboard, called VALORISE, is developed to automatize the process, support decision-makers in modeling their expectations, analyze real-time strategic scenarios, and easily explore the value-driven trade space for best-solution identification. An aeronautical application case highlights the advantages of leveraging the proposed concurrent approach to overcome the limits of traditional approaches, in which decisions about supply chain and manufacturing are addressed once the aircraft configuration is decided. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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24 pages, 7332 KiB  
Article
A Model-Based Engineering Approach for Evaluating Software-Defined Radio Architecture
by Mohammed G. Albayati, Eric B. Dano, Ravi Rajamani and Amy E. Thompson
Systems 2023, 11(9), 480; https://doi.org/10.3390/systems11090480 - 20 Sep 2023
Cited by 1 | Viewed by 2990
Abstract
In product development, important specification and design decisions must be made at various stages of the lifecycle that include design, manufacturing, operations, and support. However, making these decisions becomes more complex when a multi-disciplinary team of stakeholders is involved in system-level or subsystem-level [...] Read more.
In product development, important specification and design decisions must be made at various stages of the lifecycle that include design, manufacturing, operations, and support. However, making these decisions becomes more complex when a multi-disciplinary team of stakeholders is involved in system-level or subsystem-level architecture and design decisions. Model-Based Engineering (MBE) approaches are enabling a digital thread of connected data and models. This work demonstrates a novel MBE approach that incorporates a model-based systems engineering (MBSE) method and a multi-criteria decision-making (MCDM) method to determine the best architecture solution that aligns with stakeholder needs and objectives over multiple domains. This approach demonstrates the connection of a system descriptive model, modeled using the systems modeling language (SysML), to underlying physics-based engineering models for the purpose of better predicting the technical performance of systems during the architecture development phase. This approach is demonstrated for a common aerospace communications application, a software-defined radio. This novel MBE approach supports digital transformation at organizations and allows for earlier design validation, enabling designers to test and select the best system architecture from many candidates and validate that the design meets stakeholder needs. Full article
(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)
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