As-built schedules prepared during and after construction are valuable tools for State Highway Agencies (SHAs) to monitor construction progress, evaluate contractor's schedule performance, and defend against any potential disputes. However, previous studies indicate that current as-built schedule development methods are manual and rely on information scattered in various field diaries and meeting minutes. SHAs have started to collect field activity data in digital databases that can be used to automatically generate as-built schedules if proper computational algorithms are developed. This study develops computational algorithms and a prototype system to automatically generate and visualize project level and activity level as-built schedules during and after construction. The algorithm is validated using a real highway project data. The study is expected to significantly aid SHAs in making better use of field data, facilitate as-built schedule development, monitor construction progress with higher granularity, and utilize as-built schedule for productivity analysis.