Development of a methodology for automating the identification and localization of engineered components and assessment of its impact on construction craft productivity

Even though construction components account for more than fifty percent of the total installed costs, industry practices still solely rely on the human ability to individually track thousands of these components on the site. These primitive tracking processes are inefficient, error-prone, and can significantly hinder project performance. Thus, previous research efforts observed that up to eighteen percent of craft work-hours was attributable to the unavailability of components required for installation. Recently, though, the notion that these ineffective tracking processes can highly benefit from the implementation of information technologies (IT) has gained industry acceptance. However, the reality is that this IT influence on construction performance has not yet been addressed. The objectives of this study are (1) to develop a methodology for the automated identification and localization of engineered components on large industrial projects, and (2) to assess and to quantify the impact of this automating tracking process on project performance. The identification and localization methodology is proposed based on the combination of advanced sensing devices and localization algorithms. The integration of global positioning system (GPS) and radio frequency identification (RFID) receivers facilitates a network-free data collection process capable of detecting the presence of large numbers of RFID-tagged components almost instantly. Based on the collected data, localization algorithms precisely estimate the coordinates of the tagged items. The precision of this automated approach is validated by means of lab and field experiments. Complementarily, the impact of this localization methodology on project performance was quantified during an extensive field trial on a large industrial site. For this purpose, field records from manual and automated tracking processes were collected during the trial. Then, the influence of the automated tracking process on construction performance was determined by considering the manual approach as the baseline for comparison. The results demonstrate that information technologies can significantly enhance project performance.