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An analysis of the relationship of personnel characteristics to the performance of DD 963 class ships.

John D. May

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Abstract

Abstract : The purpose of this thesis was to analyze the relationship of fill ratios and personnel attributes to the performance of seventeen operational DD 963 class ships. Data sets were created from files provided by the Defense Manpower Data Center to determine the fill ratios and attributes. Descriptive aggregate data such as percentage of high school graduates, entry age, AFQT (Armed Forces Qualification Test) score and time in grade were selected to provide demographic information for the personnel involved. Summary CASREP (Consolidated Casualty Reporting System) data, provided by SPCC (Ship Parts Control Center), were converted to nine variables to be used as the measures of ship performance. They included total downtime, downtime due to maintenance, total number of CASREPs, and two 'readiness' indices. The relationships between these variables and personnel attributes were examined at the ship, departmental and individual rating level. Separate effects of the individual UIC's (Unit Identification Code) as well as overhaul quarters were accounted for. Personnel attributes and number of personnel vs personnel requirements had little relationship to readiness. In summary, the relationships between personnel attributes, personnel staffing levels and ship readiness measures remain to be proven.

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Abstract : The purpose of this thesis was to analyze the relationship of fill ratios and personnel attributes to the performance of seventeen operational DD 963 class ships. Data sets were created from files provided by the Defense Manpower Data Center to determine the fill ratios and attributes. Descriptive aggregate data such as percentage of high school graduates, entry age, AFQT (Armed Forces Qualification Test) score and time in grade were selected to provide demographic information for the personnel involved. Summary CASREP (Consolidated Casualty Reporting System) data, provided by SPCC (Ship Parts Control Center), were converted to nine variables to be used as the measures of ship performance. They included total downtime, downtime due to maintenance, total number of CASREPs, and two 'readiness' indices. The relationships between these variables and personnel attributes were examined at the ship, departmental and individual rating level. Separate effects of the individual UIC's (Unit Identification Code) as well as overhaul quarters were accounted for. Personnel attributes and number of personnel vs personnel requirements had little relationship to readiness. In summary, the relationships between personnel attributes, personnel staffing levels and ship readiness measures remain to be proven.

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Available abstract

Abstract : The purpose of this thesis was to analyze the relationship of fill ratios and personnel attributes to the performance of seventeen operational DD 963 class ships. Data sets were created from files provided by the Defense Manpower Data Center to determine the fill ratios and attributes. Descriptive aggregate data such as percentage of high school graduates, entry age, AFQT (Armed Forces Qualification Test) score and time in grade were selected to provide demographic information for the personnel involved. Summary CASREP (Consolidated Casualty Reporting System) data, provided by SPCC (Ship Parts Control Center), were converted to nine variables to be used as the measures of ship performance. They included total downtime, downtime due to maintenance, total number of CASREPs, and two 'readiness' indices. The relationships between these variables and personnel attributes were examined at the ship, departmental and individual rating level. Separate effects of the individual UIC's (Unit Identification Code) as well as overhaul quarters were accounted for. Personnel attributes and number of personnel vs personnel requirements had little relationship to readiness. In summary, the relationships between personnel attributes, personnel staffing levels and ship readiness measures remain to be proven.

Key concepts: Downtime, Staffing, Operations management, Descriptive statistics, Identification (biology), Engineering, Statistics, Reliability engineering

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