<p>This praxis develops a simulation-based approach to analyzing the overall reliability of complex systems with high degrees of redundancy, time varying event rates, and the potential for common cause failures. This approach is compared to traditional analytic approaches, and is shown to have some advantages, primarily by avoiding some of the simplifying assumptions used in those approaches. </p><p> Several canonical problems are solved using both traditional and simulation-based approaches to elucidate the method, and the method is then applied to more complex problems for which exact analytic solutions are not available. The method is shown to be flexible to both traditional industrial plant reliability problems and to a new class of problems involving the reliability of swarming unmanned vehicles, where there is a high degree of parallelism and dynamic formation of common cause groups. </p><p> The penultimate chapter examines the impact of common cause failures on the reliability of a swarm of unmanned vehicles performing a search mission, and develops a simulation-based approach to modeling the reliability of swarms in the presence of both independent (single vehicle) and common cause (multiple vehicle) failures. The modeling approach is exercised on a sample problem to illustrate how it can be used as part of a system design or search-planning tool for swarming unmanned vehicles. The simulation provides insight on the impact of design decisions that influence overall system reliability; it also provides metrics of success in a search scenario as a function of user-selectable parameters. </p>

<p> This dissertation introduce and empirically verify a structure of Energy Savings Performance Contracting (ESPC) perspective among clients, Energy Service Companies (ESCOs) and governments. The new approach ESPC structure model presented herein is built on the Motivation-Opportunity-Ability (MOA) theory where key influences are identified. An important component of performance contracting, the performance measurement, has been incorporated in the structure to monitor the effect on ESPC implementation success.</p><p> The proposed structure and hypothesis were verified as a current ESPC practice in the United States through an online survey. The proposed structure was analyzed to understand relationships between the stakeholders, key factors, barriers and/or practices among the constructs through the structural equation modeling (SEM) approach. Due to the complex relationship of non-normal data and small sample size compared to the number of variables, the Partial Least Square SEM (PLS-SEM) method was chosen. The survey statistical results were used to verify the ESPC-MOA structure, develop an implementation guide and identify the ESPC critical factors to help establish its implementation success.</p><p>

<p>System of Systems Engineering (SoSE) is an emerging technical discipline that is increasingly referenced in industry, primarily due to the explosion of technology over recent decades. Its meteoric rise, however, has not been followed by a comprehensive study of what truly defines this new methodology. Despite its widespread use, SoSE still lacks a cohesive, agreed-upon definition or standard curriculum. </p><p> This thesis defines a common, cross-disciplinary framework for SoSE that can be further developed through collaboration between academics and technical professionals. After establishing key SoSE concepts and their roots in traditional SE, this thesis reviews a wide spectrum of present applications and opportunities for future use of SoSE principles in hopes of encouraging a more unified understanding and development of SoSE as a technical discipline. </p>

<p> Model-Based Systems Engineering and Logistics Engineering are emerging disciplines that offer a synergy for integrating the proactive modeling of prototype R&amp;D acquisition and industrial base sustainment support into a framework that characterizes the most influential phases of the Department of Defense ground vehicle and robotics equipment life cycle. This research enhances situational awareness of upstream factors that drive the capability and capacity constraints to leveraging new technology for sustainment risk mitigation. These capability and capacity constraints include sub-optimal supply chain coordination and limited collaboration between government R&amp;D centers. This research also demonstrates how a new business model called the Defense Mobility Enterprise solves these problems, while offering an incubator for Model-Based Systems Engineering experimentation and continuous productivity improvement. Through the successful application of SysML, the modeling language of systems engineering, this research concludes with multi-model orchestration, using the momentum of commercial-off-the-shelf tools, providing a strategic lens with which to specify, analyze, design, and verify Department of Defense ground vehicle and robotics technology transition opportunities.</p><p>