Predicting construction productivity using situation-based simulation models

Construction site operations are very complex, and they involve complicated relationships among numerous tasks, factors, obstacles, risks, and uncertainties, or triggering situations that affect productivity. To improve the performance of construction operations, one needs to understand the impact these triggering situations have on productivity. The paper discusses a recently developed technique, called situation-based simulation modeling, that is used to model the triggering situations in construction to predict productivity. This tool can model the cause-and-effect relationships among various triggering situations, which previous construction models have ignored. Construction operations that were directly observed and recorded for more than 3500 person-hours served as the data source for the development of the model. The simulation results are not only able to accurately predict productivity relative to the actual productivity observed at the site, but also provide the basis for recommendations to miti...

[1]  Janaka Y. Ruwanpura,et al.  SITUATION BASED MODELING FOR CONSTRUCTION PRODUCTIVITY , 2005 .

[2]  Anthony Walker,et al.  Project Management in Construction , 1984 .

[3]  Gregory A. Howell,et al.  Reforming Project Management: The Role of Lean Construction , 2000 .

[4]  Lauri Koskela,et al.  Application of the New Production Philosophy to Construction , 1992 .

[5]  William R. Gibbs,et al.  Productivity in Construction , 1976 .

[6]  Glenn Ballard,et al.  Introducing a New Concept and Approach to Modeling Construction , 1997 .

[7]  S. Peer.  An improved systematic activity sampling technique for work study , 1986 .

[8]  Simaan M. AbouRizk,et al.  Unified Modeling Methodology for Construction Simulation , 2002 .

[9]  Simaan M. AbouRizk,et al.  BELIEF NETWORKS FOR CONSTRUCTION PERFORMANCE DIAGNOSTICS , 1998 .

[10]  Rolf A. Zwaan,et al.  The Construction of Situation Models in Narrative Comprehension: An Event-Indexing Model , 1995 .

[11]  Aminah Robinson Fayek,et al.  A Framework for Integrating Fuzzy Expert Systems and Discrete Event Simulation , 2005 .

[12]  John Christian,et al.  Effects of Delay Times on Production Rates in Construction , 1995 .

[13]  H. Randolph Thomas.  Labor Productivity and Work Sampling: The Bottom Line , 1991 .

[14]  A. K. W. Jayawardane,et al.  Construction Productivity Management , 1998 .

[15]  N. Cocchiarella,et al.  Situations and Attitudes. , 1986 .

[16]  J. D. Borcherding,et al.  Major factors influencing craft productivity in nuclear power plant construction , 1980 .

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

[18]  David Arditi.  Construction Productivity Improvement , 1985 .

[19]  Walter Kintsch,et al.  Comprehension: A Paradigm for Cognition , 1998 .

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

[21]  Simaan M. AbouRizk,et al.  Combined discrete-event/continuous simulation for project planning , 1997 .

[22]  Gregory A. Howell,et al.  SHIELDING PRODUCTION: ESSENTIAL STEP IN PRODUCTION CONTROL , 1998 .

[23]  Daniel W. Halpin,et al.  Simulation as a Tool for Pile Productivity Assessment , 2004 .

[24]  Photios G. Ioannou,et al.  Evaluation of alternative construction processes using simulation , 1995 .

[25]  Janaka Y. Ruwanpura,et al.  Carpentry workers issues and efficiencies related to construction productivity in commercial construction projects in Alberta , 2006 .