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.

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

OTEC System Concepts

1994 ◽  
Author(s):  
William H. Avery ◽  
Chih Wu
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Fossil Fuels ◽  
System Development ◽  
Cost Effective ◽  
Energy System ◽  
Economic Consequences ◽  
Early Years ◽  
The People ◽  
New Energy

Systems engineering is a top-down approach to program management and systems procurement. It optimizes the development process by ensuring that the operational, technical, and cost goals (and limitations) of a total proposed system are understood before development begins. The requirements for the “forest” are determined before the features of the “trees” are specified. It makes a basic assumption that a team endeavor under single-system management will be established with authority to define development goals and assign subsystem programs and funding. It recognizes that each system requires a unique management structure that is based on the qualifications of the people and organizations available for the total endeavor. Systems engineering begins with an authoritative request or requirement for a system that would provide new capabilities or would reduce existing problems in a significant technical activity. After personnel and level of effort for a preliminary assessment of the need are identified, the initial effort then involves these steps: 1. A precise definition is prepared of the specific operational need for which the proposed system must provide a solution. For example, this book addresses the present national need for a new energy system that can provide a practical, timely, cost-effective, and nonpolluting alternative to petroleum-based fuels for transportation. The need arises from three factors: a. The perception that an alternative to dependence on petroleum fuels for transportation must be developed to avoid severe disruption of world economies in the early years of the twenty-first century; b. Evidence that combustion of fossil fuels is causing a significant increase in the carbon dioxide content of the atmosphere (if not reduced, this could eventually produce a “greenhouse effect,” leading to large-scale changes in climate and an increase in sea level, with severe economic consequences); and c. The belief that solar energy can be used via OTEC to supply nonpolluting fuel in sufficient quantity, at low enough cost, and in time to become a practical alternative to dwindling or unavailable petroleum supplies. Failure to define the system need with sufficient clarity is a root cause of most system development difficulties.

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.

A Taxonomy for Model-Based Systems Engineering

2021 ◽  
Author(s):  
João P. Monteiro ◽  
Paulo J. S. Gil ◽  
Rui M. Rocha
Keyword(s):  
Systems Engineering ◽  
System Development ◽  
Emergent Properties ◽  
System Specification ◽  
Academic Context ◽  
Model Based ◽  
Development Processes ◽  
Expected Benefits ◽  
Model Based Systems Engineering ◽  
Execution Models

Abstract In this paper, we define Model Based Systems Engineering (MBSE) as a set of different approaches which vary in scope and in purpose, as opposed to defining it as a monolithic concept. To do so, we inductively extract common themes from papers proposing new MBSE methods based on the type of Systems Engineering (SE) artifacts produced and the expected benefits of MBSE implementation. These themes are then validated against the experiences depicted in a second set of papers evaluating the deployment of MBSE methods in practice. We propose a taxonomy for MBSE which identifies three main categories: system specification repositories, system execution models, and design automation models. The proposed categories map well onto common discussions of the nature of the SE activity, in that the first is employed in the management of system development processes and the second in the understanding of system performance and emergent properties. The third category is almost exclusively discussed in an academic context and is therefore more difficult to relate to SE practice, but its features are clearly distinct from the other two. The proposed taxonomy clarifies what MBSE is and what it can be, therefore helping focus research on the issues that still prevent MBSE practice from living up to expectations.

Model-Based Systems Engineering and Control System Development via Virtual Hardware-in-the-Loop Simulation

2010 ◽  
Author(s):  
Lawrence Michaels ◽  
Sylvain Pagerit ◽  
Aymeric Rousseau ◽  
Phillip Sharer ◽  
Shane Halbach ◽  
...  
Keyword(s):  
Control System ◽  
Systems Engineering ◽  
System Development ◽  
Hardware In The Loop ◽  
Model Based ◽  
And Control ◽  
Model Based Systems Engineering
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