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<p>Systems integration is a major endeavor in the development of a system. The goal of integration is to bring separately developed components to create the required system within both the defined schedule and the allocated budget. An entropic approach to assessing the success in attaining the goal, i.e., systems integration success, involves representing the system as a network, whose nodes are the elements of the system and whose links are the connections among the elements, and determining and tracking system network entropy. The work in this thesis considers more than two possible states for each link, explicitly assigning probabilistic measures to systems development and integration activities, and applying it to the integration of a robot used in the detection and destruction of improvised explosive devices. This work demonstrates the feasibility of applying this entropic approach to assessing systems integration success and, specifically, the feasibility of using network entropy as a metric to aid in systems integration.
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<br>Subjects: Network entropy; systems integration assessment; Markov chain; Monte Carlo simulations</div>
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Tan, Hui Fang Evelyn</div>
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