Model-based Systems Engineering Supporting Cost Analysis of Aircraft Development Process

Wang, Hao; Zhu, Shaofan; Tang, Jian; Lu, Jinzhi; Wu, Junpeng; Kiritsis, Dimitris

doi:10.1109/isse51541.2021.9582507

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The sMBSE is used to support production scheduling based on KARMA language and SMT (Chen et al 2022). In China National Key Research and Development Plan project (2020YFB1708100), aircraft onboard-maintenance-systems and aircraft development lifecycle are modeled based on KARMA (SysML and BPMN) meta-models (Wang et al 2021).…”

Section: Discussionmentioning

confidence: 99%

Semantic Model‐based Systems Engineering based on KARMA: A Research and Practice Roadmap 2025

Wang

Yan

et al. 2022

INCOSE International Symp

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Model‐based Systems Engineering is proposed as a graphical approach to support for‐malization of system artifacts across system lifecycle based on models since 1993. The previous motivation of graphical specification is to provide a unified graphical description on the perspective of systems engineering in order to formalize system architectural views, to promote communications among stakeholders and to support system analysis and verification. However, when different modeling tools are developed based on such graphical specifications, model and data interoperability across modeling tools is the biggest challenge faced by the tool venders and MBSE practitioners. Thus, semantic specification is proposed again to enhance data interoperability, such as SysML 2.0 as a possible solution. In this paper, we propose a new semantic MBSE language and framework aiming to support complex system development using a semantic two‐core mechanism: 1) KARMA language and 2) Industrial Ontologies Foundry (IOF) SE and MBSE ontology. Then, we introduce the KARMA Roadmap 2025 including technical vision, organizational views and standardization. A new KARMA open‐source modeling environment is planned to being created in order to provide MBSE application for more industrial practitioners.

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Section: Discussionmentioning

confidence: 99%

Semantic Model‐based Systems Engineering based on KARMA: A Research and Practice Roadmap 2025

Wang

Yan

et al. 2022

INCOSE International Symp

Self Cite

View full text Add to dashboard Cite

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Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

Wang

et al. 2022

ICA

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With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is challenging to implement complexity management, interface definition, and service integration across DTs. This study proposes a new concept called cognitive twin (CT) to support SoS development and operation. CTs have been defined as DTs with augmented semantic capabilities for promoting the understanding of interrelationships be-tween virtual models and enhancing the decision-making. First, CTs aim to integrate the information description of DTs across constituent systems using a unified ontology and semantic modeling technique. Second, CTs provide integrated simulations among DTs for decision-making of the SoS based on a high-level architecture (HLA). Finally, through reasoning ontology models, CTs provide decision-making options for the operations of real constituent systems. A case study on unmanned aerial vehicles (UAVs) landing on unmanned surface vehicles (USVs) is used to verify the flexibility of this approach. From the results, we find that the CT based on the proposed ontology provides a unified formalism of DTs across UAVs and USVs. Moreover, the reasoning based on the CT provides decision-making capabilities for UAVs by implementing cognitive computing to select target USVs for landing.

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Model-based Systems Engineering Supporting Cost Analysis of Aircraft Development Process

Cited by 2 publications

References 3 publications

Semantic Model‐based Systems Engineering based on KARMA: A Research and Practice Roadmap 2025

Semantic Model‐based Systems Engineering based on KARMA: A Research and Practice Roadmap 2025

Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

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