Automated Real-Time Monitoring System to Measure Shift Production of Tunnel Construction Projects

AbstractThe productivity of a tunnel construction project can deviate from the predicted plan due to many factors, such as equipment failure, weather conditions and unexpected soil characteristics. Early detection of such deviations can help management teams to reallocate resources and take necessary actions to maximize the productivity. The real-time monitoring of actual productivity would yield tremendous information toward this end, but such monitoring is difficult, especially with remote construction sites. Therefore, the common practice has been to periodically obtain manually generated aggregated productivity reports from sites. These aggregated reports are not available to both site and office management in real time and may lack detailed information. To avoid these drawbacks, the research presented in this paper proposes an automated tunnel construction monitoring system to measure the productivity of the tunnel construction in terms of shift production (meters/shift). This system computes the shi...

[1]  Herbert H. Einstein,et al.  Updating the Decision Aids for Tunneling , 2002 .

[2]  Wu Chen,et al.  Positioning and tracking construction vehicles in highly dense urban areas and building construction sites , 2007 .

[3]  Simaan M. AbouRizk,et al.  Special purpose simulation templates for tunnel construction operations , 2001 .

[4]  Jeffrey S. Bohn,et al.  Construction Project Monitoring Using High-Resolution Automated Cameras , 2010 .

[5]  Youssef M A Hashash,et al.  Integration of Construction As-Built Data Via Laser Scanning with Geotechnical Monitoring of Urban Excavation , 2006 .

[6]  Ronie Navon,et al.  Automated project performance control of construction projects , 2005 .

[7]  Mohamed A. Meguid,et al.  Excavation failure during micro-tunneling in fine sands: A case study , 2010 .

[8]  Håkan Stille,et al.  Model for Estimation of Time and Cost for Tunnel Projects Based on Risk Evaluation , 2005 .

[9]  Linda G. Shapiro,et al.  Computer Vision , 2001 .

[10]  Seyed Hossein Hashemi Doulabi,et al.  Efficient Hybrid Genetic Algorithm for Resource Leveling via Activity Splitting , 2011 .

[11]  Photios G. Ioannou,et al.  RISK-SENSITIVE DECISION SUPPORT SYSTEM FOR TUNNEL CONSTRUCTION , 2004 .

[12]  Miroslaw J. Skibniewski,et al.  A wireless network system for automated tracking of construction materials on project sites , 2008 .

[13]  Helge Toutenburg,et al.  Linear models : least squares and alternatives , 1999 .

[14]  Simaan M. AbouRizk,et al.  Special purpose simulation template for utility tunnel construction , 1999, WSC '99.

[15]  E. B. Wilson Probable Inference, the Law of Succession, and Statistical Inference , 1927 .

[16]  François Peyret,et al.  High-precision application of GPS in the field of real-time equipment positioning , 2000 .

[17]  Simaan M. AbouRizk,et al.  Analytical methods to reduce uncertainty in tunnel construction projects , 2004 .

[18]  Rafael Sacks,et al.  Assessing research issues in Automated Project Performance Control (APPC) , 2007 .

[19]  Stephen Mak,et al.  Using a real-time integrated communication system to monitor the progress and quality of construction works , 2008 .

[20]  Sy-Jye Guo Analysis of cycle excavation and productivity of large-scale rock tunnel projects — lesson learned in Taiwan , 2001 .

[21]  Simaan M. AbouRizk,et al.  Managing Performance in Construction , 2010 .

[22]  R. Malcolm W. Horner,et al.  Modeling Construction Labor Productivity , 1990 .

[23]  Changyoon Kim,et al.  Ubiquitous Sensor Network for Construction Material Monitoring , 2011 .