TY  - CONF
TI  - Automated Construction Resource Location Tracking to Support the Analysis of Lean Principles
C1  - Haifa, Israel
C3  - 18th Annual Conference of the International Group for Lean Construction
SP  - 643
EP  - 653
PY  - 2010
AU  - Cheng, Tao
AU  - Yang, Jun
AU  - Teizer, Jochen
AU  - Vela, Patricio A.
AD  - Ph.D. Candidate, School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr. N.W., Atlanta, GA 30332-0355, USA, tcheng9@gatech.edu.
AD  - Ph.D. Candidate, School of Electrical and Computer Engineering, Georgia Institute of Technology, 777 Atlantic Drive N.W., Atlanta, GA 30332-0250, USA, junyang@gatech.edu.
AD  - Ph.D., Assistant Professor, School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr. N.W., Atlanta, GA 30332-0355, USA, Phone +1 404/894, FAX 404- 894-8269, teizer@gatech.edu.
AD  - Ph.D., Assistant Professor, School of Electrical and Computer Engineering, Georgia Institute of Technology, 777 Atlantic Drive N.W., Atlanta, GA 30332-0250, USA, pvela@ece.gatech.edu.
ED  - Walsh, Kenneth
ED  - Alves, Thais
AB  - This paper presents a research framework and preliminary experimental results to automated construction resource (workforce, equipment, materials) location tracking for the purpose of advanced lean planning and rapid decision making. Based on the statement “what can be measured, can also be changed”, the research hypothesis was formulated that advanced automated remote sensing technology can measure and improve work site performance and assist decision making. The initial research scope focused on testing emerging real-time location tracking and data analysis technology (Ultra Wideband and Video) applied in capital intensive construction site settings. A literature review is presented on existing observation techniques that have been used in the analysis of lean construction operations. The research framework and technology in context to lean construction is explained next. To better understand construction operations – and in particular construction site activities related to safety and productivity – location and movements of workers, equipment, and materials were recorded in real-time. Preliminary results to field experiments demonstrate the feasibility of tracking construction resources accurately and in real-time. An outlook and applications are presented of how the collected resource trajectory information can be used in project decision making. It is envisioned, that once site resource data is collected, processed, and linked to existing schedule and work task planning, the information can play a vital role for rapid implementation of lean principles in the operational environment of construction sites.
KW  - Decision Making
KW  - Productivity
KW  - Safety
KW  - Tracking
KW  - Ultra Wideband
KW  - Workforce.
PB  - 
T2  - 18th Annual Conference of the International Group for Lean Construction
DA  - 2010/07/14
CY  - Haifa, Israel
L1  - http://iglc.net/Papers/Details/710/pdf
L2  - http://iglc.net/Papers/Details/710
N1  - Export Date: 20 April 2024
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -