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Quality Management of Pavement Condition Data Collection (2009) / Chapter Skim
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Summary
Pages 1-4

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
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From page 1...
... The literature suggests that the most efficient way to achieve high-quality pavement condition data collection services is to adopt a comprehensive, systematic quality management approach that includes methods, techniques, tools, and model problem solutions. Although the concepts of quality, quality management, quality control, and quality acceptance have been extensively used in manufacturing industrial processes, these same principles, methods, and tools have not been systematically applied to pavement data collection.
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From page 2...
... All pavement data collection service providers indicated having a formal data collection quality control plan. The main tools and methods used for quality control are: (1)
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From page 3...
... Although there appears to be common agreement that data quality is important for effective pavement management, several agencies still do not have formal quality management plans. The adoption of automated/semi-automated data collection technologies has created challenges for the roadway agencies that verify that the new equipment results are consistent with the historical practices.
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From page 4...
... The development of a workshop or training course on quality management of pavement data collection could also be beneficial.
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Key Terms

  • condition data
  • quality acceptance
  • pavement condition
  • pavement data
  • control plan

  • service providers
  • data quality
  • collection service
  • highway agencies
  • pavement management

  • provincial highway
  • software routines
  • collection quality
  • formal data
  • data meet

  • formal quality
  • quality requirements
  • collection process
  • collection technologies
  • acceptance plan

  • control segments
  • independent verification
  • production data
  • private data
  • dition data

  • data detail
  • data accuracy
  • automatic data
  • production quality
  • quality auditor


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