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A Risk-Based Model for Construction Inspection in Highways
Mohamed, Mamdouh
Mohamed, Mamdouh
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Abstract
The quality and durability of highway construction projects have been a major concern to highway agencies and contractors. Quality assurance (QA) of highway construction is defined as a tool or means by which the owner and contractors ensure that the roads are constructed in accordance with approved plans and specifications by the most economical, efficient, and safe method. To ensure the quality of highway construction projects, transportation agencies typically perform a series of tests for construction materials and inspect workmanship processes through their QA programs. Transportation agencies face the critical challenge of increased demand for highway system rehabilitation and construction work with limited inspection resources. These resources play a crucial role in asserting the quality of highway projects. The shortage of experienced QA inspection staff due to retirement or migration to the private sector has significantly impacted construction inspection capabilities. The objective of this dissertation is to develop a risk-based inspection (RBI) framework. This framework optimizes inspection and testing activities of highway construction projects based on criticality. It introduces a core list of QA inspection and testing activities for the rigid pavement, flexible pavement, bridge deck, and structural concrete. This list highly contributes to the QA of design service life and long-term performance of the highway. The prioritized list of activities may help transportation agencies allocate their limited resources to the most critical construction operations. Additionally, this dissertation provides a RBI model that serves as a risk assessment tools for highway construction quality levels and identifies causes of any quality shortfall. Bayesian belief network (BBN), fuzzy set (FS) theory, and Delphi techniques have been applied to develop the RBI model. Further, this dissertation discusses different strategies to alleviate the risk of highway construction inspection.
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Date
2022-05-31
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University of Kansas
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Keywords
Civil engineering, Bayesian belief networks, Fuzzy set, Highway, Quality assurance, Risk-based inspection