Abstract:
Construction inspection plays a critical role to ensure the quality and long-term performance of infrastructure. The current construction inspection practice at state transportation agencies (STAs) in the United States, which requires inspectors to manually gather and personally interpret the construction requirements from standard specifications, is subjective, error-prone, and time-consuming. This paper presents an intelligent database approach to automatically generate customized checklists of construction requirements at the pay item level. The proposed approach consists of three components: (1) identification of the functional requirements by consulting with the end users, (2) development of a construction inspection knowledge model via ontology to guide the database design, and (3) devising mechanisms to automate the generation of customized construction checklists for the work under inspection with all the necessary details in relation to what, when, and how to check, as well as the risks and actions when noncompliance is encountered. Specifically, the following functions now can be performed within the new system: (1) automatic generation of a customized checklist at the pay item level; (2) access to a checklist display that aligns with the repetitive/cyclical nature of construction workflows; (3) navigation between cross-referenced check items; (4) subgroupings based on responsibility, risk level, and inspection frequency; and (5) real-time links to training materials such as photos, videos, textual documents, and websites. This newly developed tool is currently being implemented and is expected to greatly reduce the workload for inspectors and enhance the effectiveness of the construction inspection process.
Supplemental Notes:
The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented here, and do not necessarily reflect the official views or policies of the sponsoring organizations and do not constitute a standard, specification, or regulation.
© National Academy of Sciences: Transportation Research Board 2021.
