Effort to Accelerate MBSE Adoption and Usage at JSC

Wang, Lui; Izygon, Michel; Okron, Shira; Garner, Larry; Wagner, Howard

doi:10.2514/6.2016-5542

Cited by 17 publications

(41 citation statements)

References 3 publications

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“…” Gregory et al 1 . caution that “the journey from Document‐Based Systems Engineering (DBSE) to Model‐Based Systems Engineering (MBSE) within an organization can be a long and winding road that requires considerable effort and expense.” This hesitancy was reflected in the frequent question of whether the steep costs of implementation and training are worth a perceived marginal return on investment 11,46–49 …”

Section: Resultsmentioning

confidence: 99%

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%

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

“…The demonstration was able to show that the IoIF SWT architecture is capable of retrieving SysML data in JSON format and then transforming it into an Excel data format. This is important not only for advancing the concept of digital thread, but also for advancing the adoption of model-based systems engineering (MBSE) by adding value to the model data [28].…”

Section: Discussionmentioning

confidence: 99%

Toward an Interoperability and Integration Framework to Enable Digital Thread

Bone

Blackburn

Kruse

et al. 2018

Systems

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This article discusses ongoing research investigating the feasibility of supporting an interoperability and integration framework to enable the digital thread, or an authoritative source of truth with current technology. The question that initiated this exploratory research was, “Is there current technology that can enable cross-domain digital artifact data sharing needed for the digital thread?” A thorough review and investigation of current state-of-the-art model-based systems engineering was performed by reviewing literature and performing multiple site visits and interviews with organizations at the forefront of digital engineering. After this initial investigation and review, a Semantic Web-enabled framework that would allow data in the thread to be captured, stored, transferred, checked for completeness and consistency, and changed under revision change control management began to be formed. This framework has gone through revisions. This paper reflects the most current demonstration of the framework and its capability of acquiring digital data, and parsing and querying the data using Semantic Web technology to generate a decision table that allows the decision data to be visualized. The article concludes with future demonstrations of the framework to further advance toward a framework that can enable a digital thread in practice.

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“…However, it relies on the quality of training data. This method cannot be used in the absence of data to support it analysis, function analysis, logic design, and physical architecture design (Wang et al (2016); Bindschadler et al, 2017;Allen, 2016).…”

Section: Model-based Systems Engineeringmentioning

confidence: 99%

A Semantic Ontology-Based Approach to Support Model-Based Systems Engineering Design for an Aircraft Prognostic Health Management System

Chen¹,

Chen²,

Hu³

et al. 2022

Front. Manuf. Technol.

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The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a powerful semantic web construction method, ontology has been widely used to express design information, such as the concepts and the relationships between them. However, traditional graphical MBSE models have a natural weakness in transforming into ontology. In this paper, a semantic MBSE method is proposed to support the transform of the ontology model. Firstly, according to the design characteristics of the aircraft PHM system, a meta-model library of the aircraft PHM system is developed to support the design and evaluation. An MBSE modeling method based on requirement analysis, function analysis, logical architecture design, and physic architecture design is applied in the PHM design process. Secondly, the semantic system modeling language KARMA based on “graph, object, property, point, relationship, role, and extension” (GOPPRRE) is used to transfer the graphical MBSE model to the semantic MBSE model, which can be easily transformed to an ontology model. Finally, an ontology based on semantic modeling is developed to describe the MBSE entities and to support MBSE design. In this paper, a case study of an aircraft fuel PHM system is carried out to validate the proposed method. Based on the developed meta-model library, a complete MBSE design process for the aircraft PHM system is realized. And then an ontology model supporting PHM system design is generated from the semantic MBSE model. The MBSE ontology provides a shareable capability to help designers communicate effectively. Quantitative analysis based on ontology is also provided to verify the complexity and scale of the MBSE design process. Moreover, logical reasoning ability can also be provided to support the early requirement traceability for MBSE design. In general, the case study results show the feasibility and effectiveness of the proposed method for the aircraft PHM system design.

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Effort to Accelerate MBSE Adoption and Usage at JSC

Cited by 17 publications

References 3 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

Toward an Interoperability and Integration Framework to Enable Digital Thread

A Semantic Ontology-Based Approach to Support Model-Based Systems Engineering Design for an Aircraft Prognostic Health Management System

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