Between 1997 and 2009, 47 major defense acquisition programs experienced cost overruns of at least 15% or 30% over their current or original baseline estimates, respectively (GAO, 2011, p. 1). Known formally as a Nunn-McCurdy breach (GAO, 2011, p. 1), the reasons for this excessive growth are myriad, although nearly 70% of the cases identified engineering and design issues as a contributing factor (GAO, 2011, p. 5). Accordingly, Congress legislatively acknowledged the need for change in 2009 with the passage of the Weapon Systems Acquisition Reform Act (WSARA, 2009), which mandated additional rigor and accountability in early life cycle (or Pre-Milestone A) cost estimation. Consistent with this effort, the Department of Defense has recently required more system specification earlier in the life cycle, notably the submission of detailed architectural models, and this has created opportunities for new approaches. In this dissertation, I describe my effort to transform one such model (or view), namely the SV-3, into computational knowledge that can be leveraged in Pre-Milestone A cost estimation and risk analysis. The principal contribution of my work is Algorithm 3-a novel, network science-based method for estimating the cost of unforeseen architectural growth in defense programs. Specifically, using number theory, network science, simulation, and statistical analysis, I simultaneously find the best fitting probability mass functions and strengths of preferential attachment for an incoming subsystem's interfaces, and I apply blockmodeling to find the SV-3's globally optimal macrostructure. Leveraging these inputs, I use Monte Carlo simulation and the Constructive Systems Engineering Cost Model to estimate the systems engineering effort required to connect a new subsystem to the existing architecture. This effort is chronicled by the five articles given in Appendices A through C, and it is summarized in Chapter 2.In addition to Algorithm 3, there are several important, tangential outcomes of this work, including: an explicit connection between Model Based System Engineering and parametric cost modeling, a general procedure for organizations to improve the measurement reliability of their early life cycle cost estimates, and several exact and heuristic methods for the blockmodeling of one-, two-, and mixed-mode networks. More generally, this research highlights the benefits of applying network science to systems engineering, and it reinforces the value of viewing architectural models as computational objects.

The Concept and Requirements Exploration process used at Virginia Tech is based on a Multi-Objective Optimization approach that explores the design space to produce a Non-Dominated set of ship design solutions ranked objectively by Cost, Risk, and Effectiveness. Prior research and effort has also been made to leverage the validation and verification of the U.S. Navy's ship synthesis design tool, ASSET, into the Virginia Tech Ship Synthesis Model. This thesis applies Design Structure Matrix theory to analyze and optimize the ASSET synthesis process by reducing or removing the feedback dependencies that require the iterative convergence process. This optimized ASSET synthesis process is used as the basis to develop a new Simplified Ship Synthesis Model (SSSM) using Commercial Off-The-Shelf (COTS) software, ASSET Response Surface Models (RSMs) and simplified parametric equations to build the individual synthesis modules. The current method of calculating an Overall Measure of Effectiveness (OMOE) used at Virginia Tech is based on expert opinion and pairwise comparison. This thesis researches methods for building a Design Reference Mission (DRM) composed of multiple operational situations (OpSits) required by the ship's mission. The DRM is defined using a Model Based Systems Engineering (MBSE) approach and an overall Ship Design System Architecture to define and understand the relationships between various aspects of the ship design. The system architecture includes the DRM and enables the development of Operational Effectiveness Models (OEMs) as an alternative to an expert opinion-based OMOE. The system architecture also provides the means for redefining and optimizing the entire ship design process by capturing the entire process and all related data into a single repository. This thesis concludes with a preliminary assessment of the utility of these various system engineering tools to the naval ship design process. / Master of Science

Evidence of the interest in enterprise architecture (EA) is seen in the number of enterprise architecture frameworks (EAF) in existence. An EAF is responsible for the realisation of an EA, and therefore acts as a container for the terminology of EA. The lack of acceptance of terms and definitions, coupled with the phenomenon of the large number of EAFs, indicate a silo type understanding of what EA is, which leads to a lack of clarity in the conceptual foundations of EA. By following a design science research (DSR) approach, a conceptual artefact (an enterprise architectonic (EAt)) is created to address the lack of clarity in the conceptual foundations of EA thinking and practice. The EAt serves as a conceptual device to represent the fundamental understanding of EA in terms of concepts and their relationships. The content of the EAt is derived from applying a structured interpretation method (SIM) to three prominent EAFs (The Open Group Architecture Framework, the Department of Defense Architecture Framework and the Zachman Framework for Enterprise Architecture). The SIM’s results are an EA understanding that consists of an EA claim: EA is similar in intent to the enterprise as a worldview is to the world. It is supported by six EA propositions:  Proposition 1: EA’s underlying theoretical knowledge is in a pre-suppositional state.  Proposition 2: EA is a description of the structure of the systems of an enterprise.  Proposition 3: EA represents the enterprise in time-oriented architectures such as an as-is, to-be and has-been architecture.  Proposition 4: EA translates the values/strategy of the enterprise into operational systems appropriate to the information society.  Proposition 5: EA provides a means to manage decisions about the IT/IS management and implementation in the enterprise.  Proposition 6: EA captures a representation of the enterprise in the form of a model or set of models. The six EA propositions are analysed through the lens of Heidegger's equipment analysis, to produce a set of architectonic elements. These elements are arranged in the EAt to create a conceptual device to support the fundamental understanding of EA. / Centre for Applied Information and Communication / Ph.D. (Information Systems)

Evidence of the interest in enterprise architecture (EA) is seen in the number of enterprise architecture frameworks (EAF) in existence. An EAF is responsible for the realisation of an EA, and therefore acts as a container for the terminology of EA. The lack of acceptance of terms and definitions, coupled with the phenomenon of the large number of EAFs, indicate a silo type understanding of what EA is, which leads to a lack of clarity in the conceptual foundations of EA. By following a design science research (DSR) approach, a conceptual artefact (an enterprise architectonic (EAt)) is created to address the lack of clarity in the conceptual foundations of EA thinking and practice. The EAt serves as a conceptual device to represent the fundamental understanding of EA in terms of concepts and their relationships. The content of the EAt is derived from applying a structured interpretation method (SIM) to three prominent EAFs (The Open Group Architecture Framework, the Department of Defense Architecture Framework and the Zachman Framework for Enterprise Architecture). The SIM’s results are an EA understanding that consists of an EA claim: EA is similar in intent to the enterprise as a worldview is to the world. It is supported by six EA propositions:  Proposition 1: EA’s underlying theoretical knowledge is in a pre-suppositional state.  Proposition 2: EA is a description of the structure of the systems of an enterprise.  Proposition 3: EA represents the enterprise in time-oriented architectures such as an as-is, to-be and has-been architecture.  Proposition 4: EA translates the values/strategy of the enterprise into operational systems appropriate to the information society.  Proposition 5: EA provides a means to manage decisions about the IT/IS management and implementation in the enterprise.  Proposition 6: EA captures a representation of the enterprise in the form of a model or set of models. The six EA propositions are analysed through the lens of Heidegger's equipment analysis, to produce a set of architectonic elements. These elements are arranged in the EAt to create a conceptual device to support the fundamental understanding of EA. / Centre for Applied Information and Communication / Ph. D. (Information Systems)