A Model-Based Systems Engineering (MBSE) approach for defining the behaviors of CubeSats

Kaslow, David; Ayres, Bradley; Cahill, Philip T; Hart, Laura; Yntema, Rose

doi:10.1109/aero.2017.7943865

Cited by 26 publications

(6 citation statements)

References 2 publications

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“…As cited by several sources, MBSE's ability to handle complexity and to improve decision‐making and consistency throughout the lifecycle is a reason for its widespread adoption in aerospace and defense industries 50,51 . In other industries, companies were usually reluctant to adopt MBSE due to the lack of mature toolsets and applications to their particular projects, which is in line with MBSE being an emerging approach 1,52–55 . Despite a few complaints, most of the analyzed sources supported the ability of MBSE to handle increasingly complex projects (33:4 Pos/Neg SM).…”

Section: Resultsmentioning

confidence: 91%

Model‐based systems engineering: Evaluating perceived value, metrics, and evidence through literature

Campo

Teper

Eaton

et al. 2022

Systems Engineering

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Although Model-Based Systems Engineering (MBSE) is quickly becoming adopted in Systems Engineering (SE), there have not been many studies evaluating literature to determine the perceived value of implementing MBSE. This research first identifies and discusses previous studies on the justification or rejection of MBSE. This study investigates how the SE community perceives the value of MBSE by coding and analyzing positive and negative descriptions of MBSE; perceived benefits and drawbacks of implementing MBSE; and the evidence and metrics used to substantiate and measure each claim about MBSE. From 60 academic sources, this study collected and coded over 2900 claims on MBSE. Our findings determine the most positive attributes of MBSE to be Verification & Validation Capability, Consistency, Reasoning, and Risk & Error Manageability, while the most negative attributes were Approach Understandability, Acceptability, Familiarity, and Approach Complexity. The most-stated benefits were Reduced Time, Better Communication/Information Sharing, Reduced Costs, and Better Analysis Capability. The most claimed drawbacks were Increased Costs, Increased Time, Increased Effort, and Worsened Capability. A large share of claims (47%) about MBSE was based on author opinions. Most claims (86%) were not substantiated by a metric.

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Section: Resultsmentioning

confidence: 91%

Model‐based systems engineering: Evaluating perceived value, metrics, and evidence through literature

Campo

Teper

Eaton

et al. 2022

Systems Engineering

View full text Add to dashboard Cite

show abstract

“…A large number of requirement-related keywords is another characteristic of this cluster. The forward design process, which starts with requirements, is an important part of the MBSE focus and is currently used intensively in modeling languages [93].…”

Section: Current Practicesmentioning

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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“…Of the methodologies described in this survey, INCOSE's Object-Oriented Systems Engineering Method (OOSEM) describes using MBSE tools to inform system requirements with the most detail (Estefan 2008). This methodology has been used to inform submarine design and CubeSat design, but in both cases, discussion focused on use case development and did not provide a specific methodology for translating functional flows to requirements (Pearce & Hause 2012) (Kaslow et al 2017). The white paper on submarine design describes the systems requirement step of their process in a few sentences: "In [this submarine effort], a requirements analysis workshop will develop several black-box scenarios for a system.…”

Section: Background and Overviewmentioning

confidence: 99%

“…The white paper on CubeSat design provides more detail in how they went from client needs to defining behavior. The team developed use cases from top level needs and then decomposed the identified behaviors to the appropriate level, but on the topic of creating English-language requirements simply stated "these actions can be captured as functional requirements of the CubeSat" (Kaslow et al 2017).…”

Section: Background and Overviewmentioning

confidence: 99%

Formulas and Guidelines for Deriving Functional System Requirements from a Systems Engineering Model

Shelton

Heisler

Sebacher

2021

INCOSE International Symp

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Within this paper, we discuss a specific approach to system‐level modeling using activities, with the goal of writing English‐language requirements for the System of Interest (SOI), and then using formulas which interact with the model to proceduralize the authorship process. This overall approach makes it possible for most technical participants in a program to do most of their development work in a collaborative modeling environment, spending most of their time dealing with technical issues rather than language issues, while implementing a rapid translation to English‐language functional requirements toward the end of the process which may eventually be automated.

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A Model-Based Systems Engineering (MBSE) approach for defining the behaviors of CubeSats

Cited by 26 publications

References 2 publications

Model‐based systems engineering: Evaluating perceived value, metrics, and evidence through literature

Model‐based systems engineering: Evaluating perceived value, metrics, and evidence through literature

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

Formulas and Guidelines for Deriving Functional System Requirements from a Systems Engineering Model

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