<p> The Systems Engineering community spends considerable effort developing system specifications during the design phase. Yet during the operational and support phase, there is a potential degradation of those specifications in the form of delayed, missed, or insufficient maintenance (i.e., maintenance that does not restore the system to the design specifications), which are commonly called departures (e.g., Structure/Weld Joint - Incorrect Electrode Usage, Valve Timing, etc.). While the impact of each departure on the system is reviewed as part of the current approval process, there is no evaluation to the equipment and/or personnel from the accumulated number of departures. </p><p> The impact of these accumulated departures is analyzed to determine if there is a correlation between these accumulated departures and casualties to equipment (documented on casualty reports that impact system availability and operational readiness) and/or mishaps to document a safety event and/or damage to property. The analysis required the development of a framework to systematically store and catalog U.S. Navy data on a select set of hulls from 2004 to 2016 specifically addressing data on 6,810 departures, 4,808 casualty reports, and 6 mishaps. A series of analyses were conducted to include (1) ensuring the hulls met the criteria of in-service (i.e., operational ready for deployment), (2) test for trends together as a class followed by this same analysis on a per hull basis, which helped define the correct correlation method, (3) Spearman’s rank-order correlation analyses as a class followed by this same analysis on a per hull basis and (4) regression analysis to determine if departures could be used to predict future casualties. The correlations and regression results suggested meaningful, statistically significant at the 0.01 level, for a majority of the relationships between the accumulated number of departures determined at the class level and for each individual hull. The framework and process that is described in this paper can be used to track and influence the number of casualty reports that are predicted to occur by controlling the number of accumulated departure from specifications. There also was no correlation determined between the accumulated departures from specifications and subsequent Mishaps and thus there was no regression analysis conducted.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10928773 |
| Date | 15 January 2019 |
| Creators | O'Toole, Raymond D., Jr. |
| Publisher | The George Washington University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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