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NCHRP Synthesis 401: Quality Management of Pavement Condition Data Collection (2009)
National Cooperative Highway Research Program Synthesis Program (NCHRPSYN)

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Flintsch, Gerardo W, McGhee, Kevin Kenneth, Transportation Research Board. "Quality Management Plans." NCHRP Synthesis 401: Quality Management of Pavement Condition Data Collection. Washington, DC: The National Academies Press, 2009.

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Front Matter (R1-R9)
Summary (1-4)
Scope and Organization (5-5)
Background (6-9)
In-House versus Service Provider Collected Data (10-12)
Issues Associated with Location Referencing (13-14)
Pavement Condition Indicators (15-15)
Time-History Data Collection Issues (16-16)
New Demands Imposed by Changing Business Practices (17-17)
Summary (18-19)
Background on Quality Management Concepts and Processes (20-20)
Quality Management Plans (21-21)
Data Management Activities (22-22)
Reference Values/Ground Truth (23-23)
Sources of Variability in Pavement Condition Data Collection (24-26)
Effects of Network Size on Quality Management (27-28)
Summary (29-29)
Quality Control (30-36)
Quality Acceptance (37-40)
Independent Verification (41-41)
Summary (42-42)
Maryland (43-44)
Virginia (45-46)
Oklahoma (47-47)
British Columbia (48-48)
Summary (49-50)
Summary of Findings (51-52)
Issues Identified (53-53)
Suggestions for Future Research (54-54)
Glossary (55-56)
References (57-60)
Appendix A - State and Provincial Agency Survey Questionnaire (61-71)
Appendix B - Service Providers Survey Questionnaire (72-76)
Appendix C - Tabular Results of the State and Provincial Agency Survey (77-103)
Appendix D - Example of Pavement Condition Data Collection Request for Proposal - Louisiana Department of Transportation and Development (104-132)
Appendix E - Example of Pavement Condition Data Collection Request for Proposal (Oklahoma DOT) (133-144)
Abbreviations used without definitions in TRB publications (145-145)

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21 International Standards Organization (ISO) known as the pendent validation and verification has been especially use- ISO 9000 series, or "family," of standards (48). These stan- ful. A third-party contractor was asked to manually check dards offer quality management guidance and identify the 10% of the data collected and analyzed through automated elements necessary to direct and control an organization with methods. This process provided a high-level check of the regard to quality. The standards lay out the requirements for deliverable tables to verify data completeness and data rea- an organization (company, public agency, etc.) to deliver sonableness, as well as a direct pavement distress compar- products and services that consistently meet customer expec- ison between the service provider automated ratings and tations and for an organization to be "certified." The Deming manual ratings from experienced pavement raters. The process cycle, plan-do-check-act, is one of the models that can be also helped identify several systematic errors (e.g., erro- used to achieve higher levels of quality. neous classification of a particular distress type). The cor- rection of these errors resulted in an 83% reduction in the One of the main concepts that have influenced the develop- pavements requiring rehabilitation, and a 22% increase in ment of the aforementioned standards is that of TQM. Total pavements requiring no maintenance. The overall effect of Quality is a process by which an organization strives to provide these changes was a decrease of $18 million in the pavement customers with products and services that satisfy its needs. The maintenance recommendation for the Interstate Highway TQM philosophy seeks to integrate all organizational functions System (51). (design, engineering, production, etc.) to focus on meeting customer needs and organizational objectives. The key prin- ciples of TQM include management commitment (plan- QUALITY MANAGEMENT PLANS do-check-act), employee empowerment, fact-based decision making, continuous improvement, and customer focus (49). A Quality Management Plan documents how the agency will plan, implement, and assess the effectiveness of its pavement Another business management approach that is closely data collection quality control and quality acceptance opera- related with quality is Six Sigma. This management philoso- tions. It describes the quality policies and procedures; areas phy, originally developed by Motorola, emphasizes setting of application; and roles, responsibilities, and authorities. The extremely high-quality objectives, collecting data, and ana- Quality Management Plan is a program-specific document lyzing results to a fine degree as a way to reduce defects in that describes the general practices of the program. It may be products and services. The name comes from the Greek let- viewed as the "umbrella" document under which individual ter sigma, which is used to denote variation from a standard quality activities are conducted. (e.g., standard deviation). The philosophy behind Six Sigma is that if you measure how many defects are in a process, you Figure 10 summarizes the state of the practice with can determine ways to systematically eliminate them and get respect to the use of formal data collection quality man- as close to perfection as possible (50). agement plans among state DOTs and Canadian provinces. Approximately one-third of the agencies (35%) already IMPORTANCE OF QUALITY DATA have a formal plan and an additional 27% are working on TO SUPPORT PAVEMENT MANAGEMENT developing such a plan. It is interesting to note, however, that a large percentage of the agencies still do not have a for- "Good" data are very important in providing effective pave- mal approach for ensuring the quality of the data and 11% of ment management. In particular, adequate quality and quantity the respondents did not know if a quality management plan of pavement condition data are a very important component existed. in a PMS. For example, accurate and temporally consistent data are critical to develop models to predict smoothness Question: Does your agency have a formal pavement and crack progression (38). These models are necessary for data collection quality management plan? developing effective multi-year preservation plans and work programs. Even when performing network-level analysis, Not errors in the data can have a significant effect on the recom- Sure mended treatments and budgetary requirements. Systematic 11% Yes 35% errors are considered especially critical at the network level, where a large volume of data is collected and errors can be No 27% compounded (51). Less critical are the random errors, because it is expected that they will offset each other if enough data are collected. Under Develop. 27% Adequate quality management can help eliminate sys- tematic errors and minimize random errors. For example, in FIGURE 10 Use of data collection quality Virginia, the introduction of a third party to provide inde- management plans.