Model‐based systems engineering: Motivation, current status, and research opportunities

Madni, Azad M.; Sievers, Michael

doi:10.1002/sys.21438

Cited by 275 publications

(206 citation statements)

References 70 publications

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“…Our task evaluation here is based on research papers from the SE literature, our hands-on experience with MBSE tools, available MBSE tool documentation, and models that we developed as needed to complete the evaluation. Our study accounted for plugins which allow these MBSE tools to integrate with third-party tools related to requirement engineering, PLM, CAD integration, analysis, simulation, design optimization, real-time and embedded development, publishing, reviewing and collaboration [12,13]. Figure 8a presents the percentage coverage of technical processes by MBSE tools.…”

Section: System Life Cycle Processesmentioning

confidence: 99%

Economic Analysis of Model-Based Systems Engineering

Madni

Purohit

2019

Systems

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In the face of ever-increasing complexity of systems and system development programs, several aerospace, automotive, and defense organizations have already begun or are contemplating the transition to model-based systems engineering (MBSE). The key challenges that organizations face in making this decision are determining whether it is technically feasible and financially beneficial in the long-run to transition to MBSE, and whether such transition is achievable given budgetary constraints. Among other cost drivers of this transition, are a new digital infrastructure, personnel training in MBSE, and cost-effective migration of legacy models and data into the new infrastructure. The ability to quantify gains from MBSE investment is critical to making the decision to commit to MBSE implementation. This paper proposes a methodological framework for analyzing investments and potential gains associated with MBSE implementation on large-scale system programs. To this end, the MBSE implementation problem is characterized in terms of: system complexity, environment complexity and regulatory constraints, and system lifespan. These criteria are applied to systems in twelve major industry sectors to determine MBSE investment and expected gains. Results from this cost-benefit analysis are used to justify investment in MBSE implementation where warranted. This approach is generic and can be applied to different sectors for economic evaluation of costs and benefits and justification of transition to MBSE if warranted.

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Section: System Life Cycle Processesmentioning

confidence: 99%

Economic Analysis of Model-Based Systems Engineering

Madni

Purohit

2019

Systems

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“…A significant finding for MBSE practitioners interested in the patterns‐based approach is the elegant execution of the playbook structure in simulation, using and reusing selected plays in different tactics, and selected tactics in different missions simply by adding the same parent activity (named for the tactic or play) to different mission models, and running the mission model to “call” the lower level models in the mission simulation. The MIO mission model example in Figure illustrates how this nesting of behavior patterns was done in LML executable models.…”

Section: Discussionmentioning

confidence: 99%

“…Figure 4 is The MASC framework demonstrated modularity in the phases, tactics, and plays that were used across different missions and within each mission. Table 1 A significant finding for MBSE practitioners interested in the patterns-based approach 36 is the elegant execution of the playbook structure in simulation, using and reusing selected plays in different tactics, and selected tactics in different missions simply by adding the same parent activity (named for the tactic or play) to different mission models, and running the mission model to "call" the lower level models in the mission simulation. The MIO mission model example in…”

Section: Discussionmentioning

confidence: 99%

A mission‐based architecture for swarm unmanned systems

Giles

Giammarco

2019

Systems Engineering

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This research applies a mission engineering approach with model‐based systems engineering foundations to formalize a swarm unmanned system design methodology and architecture. The architectural framework and methodology herein presented extend current swarm system design methods, which are primarily bottom‐up approaches focused on the behavior of individual agents. We introduce a top‐down, hierarchical approach with an overarching mission decomposed into phases, tactics, plays, and algorithms. Three unmanned aerial vehicle swarm case studies (one of which is discussed in this paper) are used to demonstrate the approach and its effectiveness in formalizing a mission‐based framework of common patterns in swarm missions that promote architecture reusability.

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“…For better understanding of the term, the area of application is investigated. The core idea of modelbased engineering (MBE) is to support the development process by using semi-formal and formal models [18] instead of written informal documents [9]. The intentions behind the use of models in development cover various aspects e.g., clear interpretation, reusability, merging of information from different sources and a possibility to better describe the reality [4,7].…”

Section: Introductionmentioning

confidence: 99%

Definition of a system model for model-based development

2019

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The term 'system model' is used in many different domains, fields of application and in various forms with different meanings. One of model-based systems engineering's targets is the generation of a system model, which is used to describe complex system aspects across multiple views of disciplines and technical domains. Often a system model generated with systems modeling language is used as a central placed model in development. Besides, there are practical approaches, where models generated with other languages are also sometimes called system models. The scope of this paper is a generic definition of the term 'system model' and its interactions with other types of models in a model-based development ecosystem. Based on the analysis of the actual situation, a concept for the definition of system models is presented, which enables the use of multiple system models and which helps to understand the interactions with other types of models. For better comprehension of a system model's role in development, a three dimensional cube for visualization of system models and specific models is presented. Coupled with the definition of the term, interactions to other approaches like product lifecycle management and the vision of a single source of truth for development are investigated and discussed.

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Model‐based systems engineering: Motivation, current status, and research opportunities

Cited by 275 publications

References 70 publications

Economic Analysis of Model-Based Systems Engineering

Economic Analysis of Model-Based Systems Engineering

A mission‐based architecture for swarm unmanned systems

Definition of a system model for model-based development

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