The Budding SV3: Estimating the Cost of Architectural Growth Early in the Life Cycle

Abstract

As the systems engineering community continues to mature model-based approaches, exciting opportunities for sophisticated, computational analysis grow. Among these possibilities, we posit and demonstrate a novel algorithm for estimating the cost of architectural changes early in the system life cycle when uncertainty is high. In particular, by treating the DoD Architecture Framework (DoDAF) Systems View 3 (SV3) as an adjacency matrix, we leverage concepts from network science to analyze the impact of architectural changes that result from the addition of a subsystem. Following this growth, we estimate the marginal increase in systems engineering effort via an explicit connection between the open academic cost model COSYSMO (Constructive Systems Engineering Cost Model) and the SV3. Based on its stochastic nature, this procedure is further implemented as a Monte Carlo simulation, allowing us to generate distributions of potential cost growth. Theoretically, this work serves as a proof of concept for further research on the integration of network science and systems engineering. Practically, the methodology provides a means for practitioners to accelerate the accuracy and fidelity of their should cost and will cost analyses early in the systems life cycle.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 2014
Accession Number
ADA624710

Entities

People

  • Matthew Dabkowski
  • Ricardo Valerdi

Organizations

  • University of Arizona

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computer Science
  • Cost Analysis
  • Cost Models
  • Cost Overruns
  • Costs
  • Department Of Defense
  • Engineering
  • Engineers
  • Industrial Engineering
  • Law
  • Life Cycles
  • Network Science
  • Operations Research
  • Systems Engineering
  • Test And Evaluation

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Economics
  • Software Engineering.