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OCR for page 51
51 CHAPTER SIX FINDINGS AND SUGGESTIONS FOR FUTURE RESEARCH Pavement data collection quality control is receiving increased lored to the use of the data and the level of decisions attention, not only because data collection is one of the most being supported. The level of detail, accuracy, and costly parts of operating a pavement management system, but coverage (and consequently "quality") required is also because data quality has a critical effect on the business different for supporting network- and project-level decisions supported by the system. To ensure that the data pavement management decisions. In general, surface collected meets the need of the pavement management process, distress (98% of respondents) and smoothness (95%) agencies are developing procedures and guidelines for quality data are collected for network-level analysis. Project- management of pavement data collection activities. The syn- level surveys typically include more detailed distress thesis reviewed quality management practices being employed surveys (oftentimes walking the section) and assess- by public road and highway agencies for automated, semi- ments of the structural capacity (71%) and frictional automated, and manual pavement condition data collection properties (55%) for specific projects. and delivery using in-house staff and contracted services. The 2. Quality Management Plan: This plan documents following sections summarize the main findings of the study how the agency plans, implements, and assesses the and provide topics for future research. effectiveness of its pavement data collection quality control, quality acceptance, and independent verifica- SUMMARY OF FINDINGS tion operations. Approximately one-third of the state and provincial highway agencies (35%) already have The concepts of quality, quality management, quality control, a formal plan and an additional 27% are working on and quality acceptance have been extensively used in manu- developing such a plan. Furthermore, agencies with facturing industrial processes. However, these same principles, larger networks were more likely to have a formalized methods, and tools have not been systematically applied to quality management plan than the smaller agencies. An pavement data collection. This is partially because in these example of the components of a quality management services the "product" is not clearly known and the reference plan is provided in Figure 24. value often is difficult to determine. The literature suggests 3. Quality Management Tools and Methods: The that the most efficient way to achieve high-quality pavement main tools/methods used for quality control and accep- condition data collection services is to adopt a comprehensive, tance by state and provincial highway agencies are the systematic quality management approach that includes meth- following: ods, techniques, tools, and model problem solutions. Calibration/verification of equipment and meth- ods before the data collection (used by 94% of the Independent of the mechanism used to collect the data, agencies for quality control and by 80% for quality in-house or through a service provider, a complete quality acceptance), management system may include a clearly documented qual- Testing of known control segments before data col- ity management plan, detailed and timely quality control and lection (94% for quality control and 73% for quality acceptance procedures, and established guidelines to monitor acceptance), the entire data collection process. Before data collection, equip- Testing of known control or verification segments ment is properly calibrated, procedures clearly defined and during data collection (81% for quality control and documented, and personnel trained. During data collection, 71% for quality acceptance), and pavement condition data is verified by a variety of possible Software routines for checking the reasonableness methods to ensure data accuracy, consistency, and complete- (57% for quality control and 71% for quality accep- ness during the collection effort. After data collection is com- tance) and completeness (55% for quality control and plete, the data may then be validated before acceptance. 61% for quality acceptance) of the data. The main findings concerning the state of the practice and Other promising quality management techniques knowledge of quality management of pavement condition that are not yet as commonly used include: data are the following: Analysis of time-series data both at the project and 1. Data Quality Requirements: Data collection prac- network-level (used by 42% of the agencies for qual- tices and quality management processes may be tai- ity control and by 50% for quality acceptance),

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52 Quality Acceptance Define: Before Data Collection o Data accuracy, precision, and resolution Define & set up: o Rating system/ protocol o Scope of work o Specific requirements/ specifications o Project schedule o Project team Known control site testing & review Select control sites and ground truth Quality Control determination Equipment calibration & acceptance Setup collection subsystems Rater Training (certification) Control site data collection and Standardization of operation procedures processing Develop quality check program Equipment/method validation using control sites Quality Acceptance Pilot feedback Blind (or known) control site testing During Production Periodic raw data review (e.g., weekly) (Data Collection & Processing) Periodic processed data review (e.g., monthly) Pilot data collection & processing Production data collection Quality Control Production data processing Equipment inspection Control site (known & blind) testing Real-time data checks Reruns and exceptions Raw data checks (e.g., daily) Processed data checks (e.g., weekly) Control site data monitoring Rater consistency monitoring File and project tracking/ documentation Quality Acceptance Final data review & feedback Review for missing segments (e.g., GIS-based) After Data Collection Production Sampling and statistical comparisons Independent quality assurance Data assembly Time series comparisons Exception flags Data Delivery Quality Control Final Reports Check for missing segments or data elements Final database software checks Verification of distress ratings (e.g., using time series comparisons) FIGURE 24 Example of quality management plan components [after Rada et al. (67 ) and Zhang and Smadi (73)]. Independent (quality control or acceptance) verifi- quality control plan or require the service provider to cation and validation of the pavement condition data develop such a plan. All pavement data collection ser- by an independent quality auditor (4% for quality vice providers indicated having a formal data collection control and 12% for quality acceptance), and quality control plan. Use of blind site monitoring during the production quality acceptance process (24% for quality control Based on the examples reviewed, a comprehensive and 21% for quality acceptance). quality control plan typically includes the following 4. Quality Control includes actions and considerations elements: necessary to assess and adjust production processes to obtain the desired level of quality of pavement condi- Clear delineation of the responsibilities, tion data. Approximately two-thirds of state and provin- Documented (and available) manuals and procedures, cial highway agencies have a formal data collection Training requirements for the survey personnel,