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Optimal Maintenance Crew Composition and Enhancement of Crew Productivity

File Language:
English


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  • Edition:
    Final report.
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  • 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.
  • Format:
    PDF
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  • File Type:
    Filetype[PDF - 547.62 KB]
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  • Main Document Checksum:
    urn:sha256:eb9868edf94b8d37a1406e5564e04371668e1848418030e1c3c40d8f5c67ea0e
File Language:
English
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