Trends in Occurrences of Systems Engineering Topics in Literature

Bhatia, Garima; Mesmer, Bryan

doi:10.3390/systems7020028

Cited by 9 publications

(7 citation statements)

References 43 publications

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“…Second, due to MBSE's relatively new emergence in the SE community, 28 researchers may be publishing with more positive attitudes about MBSE due to the pressures to publish on MBSE and to secure research funding. As a result of MBSE's rapid popularity, researchers may believe MBSE will remain a presence in engineering research.…”

Section: Resultsmentioning

confidence: 99%

“…Between January 2020 and August 2021, key terms (shown in Table 1) were searched in Google Scholar . While there has been some historical debate on Google Scholar's coverage, 23–25 more recent studies have concluded it is a powerful search tool for systematic reviews, 26–29 providing broader coverage than journal searches and prioritizing highly cited works. Fifteen neutral search terms were used to identify sources.…”

Section: Methodsmentioning

confidence: 99%

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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: 99%

Section: Methodsmentioning

confidence: 99%

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

Campo

Teper

Eaton

et al. 2022

Systems Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…Using this logic, we are able to include a large number of relevant documents within this review that may have otherwise been missed, enabling a more comprehensive assessment of SBD. We refer to this set of documents as Group B from this point forward 1,66–122 . We provide the complete listing for all Group B documents in Table 2.…”

Section: Methodsmentioning

confidence: 99%

“…The demanding requirements of modern systems, and their complexity, require the development of new systems engineering methodologies 1 . A system's complexity is the product of its individual components and subsystems, their interaction with each other, and the system's interaction with its operators and maintainers, other systems, and ultimately its operating environment.…”

Section: Introductionmentioning

confidence: 99%

Set‐based design: The state‐of‐practice and research opportunities

Shallcross¹,

Parnell²,

Pohl

et al. 2020

Systems Engineering

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Increasing system complexity has provided the impetus to develop new and novel systems engineering methodologies. One of these methodologies is set‐based design (SBD), a concurrent design methodology well suited for complex systems subject to significant uncertainty. Since the 1990s, numerous private, public, and defense sector design programs have successfully implemented SBD. However, concerns regarding SBD's complexity, tendency toward qualitative methods, and lack of quantitative tools have limited its use. To address these issues, our research surveys 122 refereed journal articles and conference papers to assess SBD's state‐of‐practice and identify relevant research opportunities. To accomplish these tasks, we perform a structured literature review to identify and assess relevant and influential research. We found that SBD's state‐of‐practice relies heavily upon decision and tradespace analysis with increasing emphasis on uncertainty modeling and MBSE. We found that the majority of SBD research consists of quantitative methodologies focusing on component and small system applications. We also found that complex system applications used mostly qualitative methodologies. We identify SBD research opportunities for requirements development, MBSE, uncertainty modeling, multiresolution modeling, adversarial analysis, and program management. Finally, we recommend the development of a comprehensive SBD methodology and toolkit, suited for complex system design across all stages of the product development life cycle.

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“…Model-Based Systems Engineering is presently the fastest growing topic in systems engineering (Mesmer, 2019). MBSE is a relatively new engineering practice in which engineers use models to detail and even simulate a system across its lifecycle (Gardan & Matta, 2017).…”

Section: Relevance Of This Studymentioning

confidence: 99%

Preventing MBSE Amnesia through Role‐Based Knowledge Management

Fitzsimmons

2023

INCOSE International Symp

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The problems of knowledge management (KM) have changed in the last thirty years since its introduction, as evidenced by the decrease in searches for “knowledge management” and the up‐tick in Google trends for searches on “big data.” With the introduction of Web 2.0, the amount of data available within a company has exploded, but a company's technology for navigating that data has not necessarily kept up. Consequently, companies are at high risk for organizational knowledge loss. This is particularly acute in new technologies that suffer from a labor shortage, such as Model‐Based Systems Engineering (MBSE).To reduce this risk, best practices for knowledge taxonomy and knowledge navigation are explored within this paper. A systematic literature review will generate categorization data for MBSE topics and suggest organization for a Knowledge Management System (KMS) that will facilitate user interaction. Gaps in the current research of MBSE are identified for future research. Future research may also include organizational surveys to evaluate adoption and perceived effectiveness of the recommended best practices.

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Trends in Occurrences of Systems Engineering Topics in Literature

Cited by 9 publications

References 43 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

Set‐based design: The state‐of‐practice and research opportunities

Preventing MBSE Amnesia through Role‐Based Knowledge Management

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