scholarly journals A Tensor-Based Formulation of Hetero-Functional Graph Theory

2021 ◽  
Author(s):  
Amro M. Farid ◽  
Dakota J. Thompson ◽  
Wester Schoonenberg
Keyword(s):  
Graph Theory ◽  
Systems Engineering ◽  
Large Scale ◽  
Engineering Systems ◽  
Model Based ◽  
System Concept ◽  
Functional Graph ◽  
Multiple Graph ◽  
Model Based Systems Engineering ◽  
Form System

Abstract Recently, hetero-functional graph theory (HFGT) has developed as a means to mathematically model the structure of large-scale complex flexible engineering systems. It does so by fusing concepts from network science and model-based systems engineering (MBSE). For the former, it utilizes multiple graph-based data structures to support a matrix-based quantitative analysis. For the latter, HFGT inherits the heterogeneity of conceptual and ontological constructs found in model-based systems engineering including system form, system function, and system concept. These diverse conceptual constructs indicate multi-dimensional rather than two-dimensional relationships. This paper provides the first tensor-based treatment of hetero-functional graph theory. In particular, it addresses the “system concept” and the hetero-functional adjacency matrix from the perspective of tensors and introduces the hetero-functional incidence tensor as a new data structure. The tensor-based formulation described in this work makes a stronger tie between HFGT and its ontological foundations in MBSE. Finally, the tensor-based formulation facilitates several analytical results that provide an understanding of the relationships between HFGT and multi-layer networks.

Insights from Large Scale Model Based Systems Engineering at Boeing

2016 ◽  
Vol 26 (1) ◽  
pp. 542-555 ◽  
Author(s):  
Robert Malone ◽  
Brittany Friedland ◽  
John Herrold ◽  
Daniel Fogarty
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Scale Model ◽  
Model Based ◽  
Large Scale Model ◽  
Model Based Systems Engineering

Managing Semantic Consistency in Model-Based Systems Engineering Using a Matrix Structure

2012 ◽  
Author(s):  
Yun Ye ◽  
Marija Jankovic ◽  
Jean-Claude Bocquet
Keyword(s):  
Systems Engineering ◽  
Modeling Languages ◽  
Matrix Structure ◽  
Engineering Systems ◽  
Semantic Consistency ◽  
Consistency Management ◽  
Model Based ◽  
Information Transformation ◽  
The Matrix ◽  
Model Based Systems Engineering

Model-Based Systems Engineering (MBSE) currently lacks a formalized way of managing modeling consistency. This paper presents a new methodology for semantic consistency management in MBSE. At its core, a matrix structure which extends the Multiple Domain Matrix (MDM) and Engineering Systems Matrix (ESM) is used to organize semantic relations between modeling elements created by using various modeling languages and tools, and to represent how they change over time. In addition, this paper describes how the new matrix can be automatically maintained by a plug-in module which manages the bidirectional information transformation between the model and the matrix. We show that the utilization of our methodology has potential in avoiding ambiguous namings in models, enhancing the traceability of modeling elements as well as reducing manual work. A real world engineering use case with air-conditioning is used to show the utilization of our methodology.

scholarly journals Economic Analysis of Model-Based Systems Engineering

Systems ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 12 ◽  
Author(s):  
Azad Madni ◽  
Shatad Purohit
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Cost Benefit Analysis ◽  
System Development ◽  
Cost Benefit ◽  
Cost Effective ◽  
Model Based ◽  
Regulatory Constraints ◽  
Long Run ◽  
Model Based Systems Engineering

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.

scholarly journals A Conceptual Framework for Consistency Management in Model-Based Systems Engineering

2011 ◽  
Author(s):  
Sebastian J. I. Herzig ◽  
Ahsan Qamar ◽  
Axel Reichwein ◽  
Christiaan J. J. Paredis
Keyword(s):  
Systems Engineering ◽  
Tool Support ◽  
Engineering Systems ◽  
Consistency Management ◽  
Model Based ◽  
Complex Engineering ◽  
External Consistency ◽  
Challenging Question ◽  
Model Based Systems Engineering ◽  
Complex Engineering Systems

Developing complex engineering systems requires the consolidation of models from a variety of domains such as economics, mechanics and software engineering. These models are typically created using differing formalisms and by stakeholders that have varying views on the same problem statement. The challenging question is: what is needed to make sure that all of these different models remain consistent during the design process? A review of the related literature reveals that this is still an open challenge and has not yet been investigated at a fundamental level within the context of Model-Based Systems Engineering (MBSE). Therefore, this paper specifically focuses on examining the fundamentals of consistency management. We show that some inconsistencies cannot be detected and come to the conclusion that it is impossible to say whether or not a system is fully consistent. In this paper, we first introduce a mathematical foundation to define consistency in a formal manner. A decision-based approach to design is then studied and applied to the development of a real-world example. The research reveals several distinct types of inconsistencies that can occur during the design and development of a system. We show that these inconsistencies can be further classified into two groups: internal and external consistency. From these insights, the ontology of inconsistencies is constructed. Finally, requirements for possible tool support and methods to identify and manage specific types of consistency issues are proposed.

Informationsqualität in der Produktentwicklung: Modellbasiertes Systems Engineering mit expliziter Berücksichtigung von Unsicherheit/Information Quality in Product Engineering: Model-Based Systems Engineering in Explicit Consideration of Uncertainty

Konstruktion ◽  
2020 ◽  
Vol 72 (11-12) ◽  
pp. 76-83
Author(s):  
Jens Pottebaum ◽  
Iris Gräßler
Keyword(s):  
Systems Engineering ◽  
Information Quality ◽  
Engineering Model ◽  
Model Based ◽  
Product Engineering ◽  
Explicit Consideration ◽  
Model Based Systems Engineering

Inhalt Unscharfe Anforderungen, verschiedene Lösungs-alternativen oder eingeschränkt gültige Simulationsmodelle sind Beispiele für inhärente Unsicherheit in der Produktentwicklung. Im vorliegenden Beitrag wird ein modellbasierter Ansatz vorgestellt, der das industriell etablierte Denken in Sicherheitsfaktoren um qualitative Aspekte ergänzt. Modelle der Informationsqualität helfen, die Unsicherheit von Ent- wicklungsartefakten beschreibend zu charakterisieren. Mittels semantischer Technologien wird Unsicherheit so wirklich handhabbar – nicht im Sinne einer Berechnung, sondern im Sinne einer qualitativen Interpretation. Dadurch entsteht wertvolles Wissen für die iterative Anforderungsanalyse, die Bewertung alternativer System-Architekturen oder für die Rekonfiguration von Simulationen.

scholarly journals An Approach to Complement Model-Based Vehicle Development by Implementing Future Scenarios

2021 ◽  
Vol 12 (3) ◽  
pp. 97
Author(s):  
Christian Raulf ◽  
Moritz Proff ◽  
Tobias Huth ◽  
Thomas Vietor
Keyword(s):  
Systems Engineering ◽  
Holistic Approach ◽  
Future Scenarios ◽  
Worst Case ◽  
System Architectures ◽  
Vehicle Development ◽  
Model Based ◽  
Scenario Technique ◽  
Stakeholder Needs ◽  
Model Based Systems Engineering

Today, vehicle development is already in a process of substantial transformation. Mobility trends can be derived from global megatrends and have a significant influence on the requirements of the developed vehicles. The sociological, technological, economic, ecological, and political developments can be determined by using the scenario technique. The results are recorded in the form of differently shaped scenarios; however, they are mainly document-based. In order to ensure a holistic approach in the sense of model-based systems engineering and to be able to trace the interrelationships of the fast-changing trends and requirements, it is necessary to implement future scenarios in the system model. For this purpose, a method is proposed that enables the consideration of future scenarios in model-based vehicle development. The procedure of the method is presented, and the location of the future scenarios within the system architectures is named. The method is applied and the resulting system views are derived based on the application example of an autonomous people mover. With the help of the described method, it is possible to show the effects of a change of scenario (e.g., best-case and worst-case) and the connections with the highest level of requirements: stakeholder needs.

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