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This project examines technician staffing levels in modern public transit fleets and provides guidance on evaluating local needs, modeling changes, and improving staffing practices. The findings are outlined in a guidebook and supported by an interactive staffing tool.
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Technician Staffing Levels for Modern Public Transit Fleets TCRP Project E-10 Summary
TCRP E-10 Project Scope • Analysis of NTD Data, and surveys of 68 • Survey of existing data and outreach to transit agencies to identify main factors driving technician staffing levels • Develop Interactive Staffing Tool to evaluate local needs and model fleet or maintenance practice changes • Develop Guidebook explaining application of findings and how to use Staffing Tool
Analysis of NTD Data • Reviewed NTD submissions from 321 agencies • Correlations identified in several areas: • Between agency size and staffing ratios • Between spare ratio and staffing ratios • Duty cycle and miles based staffing ratios • Data was widely distributed; many outliers might be mistakes in the submission of data or misunderstanding of NTD definitions • Could not really compare “apples to apples”
Detailed Staffing Questionnaires • 68 Participating Agencies • Diversity of Size • Diversity of Geography • Most agencies found it very difficult to provide confident data for the breadth of information sought • A main goal – identifying the right fleet with the right staff • e.g. adjusting for outsourced fleets or maintenance staff maintaining non-transit vehicles
Summary of Correlations • Strong correlation between variable and staffing level: • Fleet Size (for core maintenance as well as overall) • Fleet Composition (articulated buses / cut-aways) • Level of Outsourcing
Summary of Absent Correlations • Small or no correlation between variable and staffing level • Spare ratio (small correlation, but not as big as NTD data) • Duty Cycle (Fleet mph) (small correlation, not as big as NTD data) • Fleet age (very small) • % of time on scheduled maintenance • % of fleet using alternative fuels Most correlations identified were not as strong as found in NTD Data, but data set much more reliable
Limitations of Data • Breakdown of hours by type of maintenance seems unreliable • Definition of “Scheduled” and “Unscheduled” maintenance varied • Definitions of “Productive time” varied – some based on contract, others actual timesheets
Interactive Staffing Tool The Bus Maintenance Staffing Calculator has three related purposes: • Compare actual current maintenance staffing levels with agencies in your peer group • Planning tool to determine necessary staffing levels for your particular maintenance operation based on existing factors • To model possible changes to maintenance policy to determine the impact it will have on your maintenance staffing levels.
Interactive Staffing Tool – Unscheduled Maintenance and Repairs