Manpower and Efficiency Study of the Manns Harbor Shipyard through Data Envelopment Analysis
1 online resource (192 pages) : PDF
University of North Carolina at Charlotte
The NCDOT Ferry Division (NCDOT-FD) self-performs preventative maintenance, emergency maintenance, and scheduled overhauls on a continual basis with manpower staffing to support the North Carolina Ferry Service’s (NCFS) ability to continue to operate and provide the high level of services provided to North Carolinians and visitors to the state’s east coast. Establishing performance targets for marine maintenance and repair operations can be challenging for management due to the multitude of factors that can potentially influence productivity, efficiency, and manpower requirements. The aim of this study is to measure and evaluate the efficiencies of the NCDOT-FD maintenance and repair operations using Data Envelopment Analysis (DEA). The use of DEA allows for multiple factors affecting maintenance productivity to be accounted for and allows the sources of inefficiencies in maintenance operations to be identified through examination of efficient or "best practice" DMUs. Results presented in this study are used to develop an overall strategic plan for enhanced decision-making with regards to labor and resource requirements, maintenance scheduling, and management strategies for the NCDOT-FD. Inefficient maintenance operations are identified through DEA evaluation, and recommendations for increased efficiency and productivity of these operations are provided through analysis of several quantitative and qualitative factors. Additionally, performance benchmarks provided in this paper can be used as an early warning system for inefficient shipyard maintenance operations. The use of quantified factors in the development of an overall strategic plan for manpower needs may be used for both short and long-term planning to provide an analytical approach for what is typically subjective judgement in determination of staffing and scheduling needs, organizational structure, and performance targets.
Construction & Facilities Mgmt
Mayo, GlendaChen, Don
Thesis (M.S.)--University of North Carolina at Charlotte, 2018.
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