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<p>A method is developed for determining how to implement sensors and data fusion systems for shipboard use in new or backfit warship designs. The underlying goal of proper implementation of new automation systems is to improve the operational readiness of the ship while simultaneously reducing crew size and operating costs. The thesis entails defining the method and then using it to determine the information requirements for the efficient implementation of automation technology into ship systems at multiple levels, with a primary focus at the platform level (where the operator interface resides). This includes categorizing the types of information (operational, casualty, combat, logistic, etc) and developing a schema by which each type of information is further defined and presented as an aid to the human operator. Raw sensor data is not the same as information in this context, rather information is the result of processing and analyzing raw sensor data. Information discriminators include refresh rates, frequency and extent of backup/historical logging, levels of data access, levels of automation control, levels of diagnostic and prognostic aids, and types of displays. A proposed machinery Health Monitoring System (HMS) for Gas Turbine Generators (GTG) for the current and future U.S. Navy Destroyers is examined as a case study to demonstrate the applicability of the implementation method developed in the thesis. Information requirements to support situational awareness for effective and efficient operator performance in a reduced crew environment are identified for the HMS. The required information is based on realistic shipboard scenarios, technical publications and expert interviews relating to the GTGs. Estimates of possible reductions of crew size from implementing the machinery HMS and the resultant costs and benefits of the technology over the life of the ship are analyzed.
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<br>Subjects:</div>
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Murphy, Brian P.</div>
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