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Optimal Maintenance Crew Composition and Enhancement of Crew Productivity
  • Published Date:
    2008-08-01
  • Language:
    English
Filetype[PDF-547.62 KB]


Details:
  • Publication/ Report Number:
  • Resource Type:
  • Geographical Coverage:
  • Edition:
    Final report.
  • NTL Classification:
    NTL-HIGHWAY/ROAD TRANSPORTATION-Construction and Maintenance ; NTL-PLANNING AND POLICY-PLANNING AND POLICY ; NTL-SAFETY AND SECURITY-Human Factors ;
  • Abstract:
    The South Carolina Department of Transportation dedicates a large portion of both its budget and other resources to the maintenance of the State’s transportation infrastructure. In order to maximize the efficiency and productivity of the State’s highway maintenance workforce, the SCDOT partnered with Clemson University to research the performance of these maintenance crews. The goal of the research is to begin to identify optimal crew compositions, if possible, and to enhance crew productivity. Data was collected from the SCDOT Highway Maintenance Management System (HMMS) and crew rankings were developed based on several pre-determined performance criteria. These rankings were then used to identify the top performing crews based on work description and county type. Once crew rankings were identified, the top crews were analyzed to determine the crew configurations for each activity that produced the optimum results. Optimal equipment utilization was also analyzed and improved equipment allocation specifications were developed. A detailed survey of the SCDOT maintenance workforce was conducted at six county maintenance offices to supplement the HMMS data and further generate descriptors and characteristics of the top performing crews. The counties for this survey were chosen to be representative of the different areas throughout the state of South Carolina- primarily urban counties, mixed urban and rural counties, and primarily rural counties. Both maintenance workers and maintenance engineers participated in the survey with a total of 382 surveys collected. The data collected from these surveys included demographic information on each worker, information about crews, and opinion data relating to maintenance performance standards and the worker’s understanding of those standards.
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