Statistical Analysis and Sampling Standards for Maintenance Management Quality Assurance (MMQA)

Maintenance management is very critical to the efficient allocation of resources and greater efficiencies in work processes. State departments of transportation (DOTs) need to continuously plan maintenance activities to monitor and maintain their highways, bridges, and other transportation infrastructures. Considering the limited budget and resources, maintenance activities need to be carefully planned and deployed such that the field inspections for measured conditions are conducted appropriately and statistically representative. It is thus necessary to develop a standardized statistical method to determine the samples (frequency and amount) to be collected to streamline productivity and ensure maintenance quality. This project will also develop a methodological framework for compiling, processing and statistically analyzing the data from sampled field inspections. Resampling statistical method might be used here in case the collected data are not significantly representing the “true” measurement. The framework will be able to determine the overall conditions of the system based on the collected sample data. It is critical to streamline the process of sampling field inspection sites through developing a statistical framework. An effective sampling method ensures that the items chosen to be measured from the entire “population” is statistically represented. Instead of inspecting all the sites available, the sampling method can identify a limited number of sites for inspection yet accurately represent the conditions of the overall system. The proposed statistical method would be effective to achieve the satisfying accuracy with significantly less resource and funding. Upon the collection of measured items, it is of great importance to report the finding in a manner that all maintenance levels are fully aware of the quality of maintenance of the areas that are pertinent to them. The proposed methodological framework will achieve this by generating a transferable analytical procedure to determine the overall conditions of the system, which provides references for senior leaders to prioritize the maintenance activities.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590
  • Project Managers:

    Kline, Robin

  • Performing Organizations:

    University of Utah, Salt Lake City

    College of Engineering, Department of Civil Engineering
    Salt Lake City, UT  United States  84112-0561
  • Principal Investigators:

    Liu, Xiaoyu Cathy

  • Start Date: 20150731
  • Expected Completion Date: 20180731
  • Actual Completion Date: 0
  • Source Data: MPC-494

Subject/Index Terms

Filing Info

  • Accession Number: 01579920
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: DTRT13-G-UTC38
  • Files: UTC, RiP
  • Created Date: Oct 27 2015 4:42PM