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Leveraging radio frequency technology identification for productivity analysis in high-rise construction

Until recent developments, labor productivity had been analyzed manually requiring time-consuming work and the possibility of human error. Past research has shown the multitude of benefits obtained from implementing radio frequency identification technology within various construction sites including asset tracking, inventory management, and on-site security upgrades. Additional construction improvements can be identified in terms of productivity analysis of work crews, material transport, and the overall approach to a project to determine whether the construction process is operating at maximum efficiency or can be adjusted to improve its effectiveness. This paper presents the results of implementing radio-frequency identification technology and provides a study of labor productivity analysis for a window replacement project on a high-rise construction site. This extensive study tracks the efficiency of a buck hoist worker and material lift system for transportation and illustrates the applicability of the technology despite the presence of numerous signal impeding obstacles located throughout the site.
These issues are resolved with an effective automated location and time tracking system that work in both an indoor and outdoor environment simultaneously with a data recording software and database. The in-house development of the database allows for timely information retrieval of various items of interest in this study and requires less
The experimental results show that RFID technology has the capacity to work and produce useful data for labor productivity purposes in an ever-changing construction environment. The research further recognizes relevant information regarding system optimization and worker feedback for future use.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/39625
Date12 April 2010
CreatorsSedehi, Arya John
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Detected LanguageEnglish
TypeThesis

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