UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    An Analysis of the Coast Guard's Surface Fleet Reliability Program for Medium Endurance Cutters
    (2011) Koski, Heidi Landry; Herrmann, Jeffrey; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The United States Coast Guard continues to conduct major environmental and humanitarian response efforts in addition to the other mandated missions that must be performed. In 2009, the Coast Guard Surface Forces Logistics Center implemented a reliability engineering program in an effort to improve the availability of its aging surface fleet. This thesis is an exploratory analysis of the current status of the newly implemented reliability engineering program using Soft Systems Methodology (SSM) and statistical analysis techniques with the objective of determine how the shift to reliability-centered maintenance approaches and procedures has affected the availability of the medium endurance cutters, which have long been the workhorses of the modern Coast Guard. A key goal of this work is to determine what improvements can be made to the current reliability engineering program to enable the US Coast Guard to better achieve its mission. The SSM analysis discovered several key issues including procedures, personnel training, data mining, and data reporting. Further, the analysis led to examination of eight (8) years of cutter machinery failure data as a measure to transform cutter maintenance activities into constructive mission availability information using Goal Tree - Success Trees and Boolean logic. This preliminary analysis revealed lower than desired availability percentages and a decrease in cutter availability over time. The root causes for these results are examined and found to include program implementation issues, lack of proper training, a lack of adequate funding, the age of existing fleet assets, and the Coast Guard culture. Key research questions are answered and several key opportunities for improvement are identified. Several next steps or areas for future work are proposed. A more detailed analysis of the maintenance data could assist in improving the allocation of maintenance funding and logistics support. Additionally, analyzing the data by cutter operating location and associated maintenance costs could provide useful information regarding resource allocation. With the completion of these steps, the Coast Guard can adapt its program to fit the needs of the service.
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    Risk and Economic Estimation of Inspection Policy of Periodically Tested Repairable Components
    (2005-08-02) Barroeta, Carlos Eduardo; Modarres, Mohammad; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This report presents a model to identify the optimal time between surveillance tests and overhaul frequency of components whose failures are detected upon inspection. The model is based on minimizing the total cost per unit time during the component renewal cycle. It considers the component availability assuming that the unit is "as old" after tests and repairs and "as new" after overhauls. The model takes into account costs associated with tests and maintenance, as well as potential losses related to unavailability. General conditions and a case study are discussed to evaluate the effect of costs, maintenance task durations, and the uncertainty of the reliability parameters on the optimal inspection policy of typical tested components. This report also discusses the advantage of the cost-based optimization versus the traditional approach based on maximal availability.