Browsing by Subject "Construction industry--Automation"
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Item Development of a methodology for automating the identification and localization of engineered components and assessment of its impact on construction craft productivity(2008-08) Grau Torrent, David, 1970-; Caldas, Carlos H.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.Item Human-assisted fitting and matching of objects to sparse point clouds for rapid workspace modeling in construction automation(2003-08) Kwon, Soon-wook, 1968-; Haas, Carl T. (Carl Thomas); Liapi, Katherine A.Item Spatial information acquisition and its use for infrastructure operation and maintenance(2004-05) Kim, Changwan, 1972; Haas, Carl T. (Carl Thomas)Site modeling can be useful in various safety-enhancement applications and for as-built data acquisition. For example, simulation-based on-site modeling may assist an equipment operator to avoid incidents that result in human injury or death (or damage to equipment and materials) on construction sites. Also, site modeling is required for realtime applications such as equipment control and as-built data acquisition. Site-modeling methods that are currently in use, including 3D CAD and dense 3D scanning systems, have certain limitations, in that they are time consuming and labor intensive and require high performance computers. This dissertation presents a rapid, on-site, spatial-modeling method using a “sparse point cloud” approach that represents construction sites in an efficient manner. The various procedures used in the modeling process, including a convex-hull algorithm, workspace partitioning, and an algorithm that merges model subsets from different locations to generate construction-site scenes, were developed. Experiments have been conducted to verify the accuracy and speed of the system, as well as its applicability to the representation of actual construction sites. The results of the experiments performed on actual construction sites were presented; as are case studies of the modeling method per se. Experiments of the applications of the proposed sitemodeling method to the simulation of obstacle avoidance in the operation of equipment on an industrial construction project were conducted. The experimental results indicated that the proposed spatial-modeling approach has potential for effective use in a broad class of applications in the construction industry.