TECHNICAL PAPERS
Jul 15, 2004

Process versus Data Oriented Techniques in Pile Construction Productivity Assessment

Publication: Journal of Construction Engineering and Management
Volume 130, Issue 4

Abstract

A large number of problems faces the installation of pile (drilled shaft) foundations: unseen subsurface obstacles, lack of contractor experience, site planning, etc. These problems make it difficult for the estimator to assess the pile construction productivity and cost. Several techniques might be good candidates for this assessment problem. A fundamental question arises: which technique is the most appropriate to solve this assessment problem? This study focuses on answering this fundamental research question. Data were collected through designed questionnaires, site interviews, and telephone calls to experts in different construction companies. Four different techniques were listed as candidates to solve this problem: deterministic, simulation, multiple regression, and artificial neural network (ANN). They were categorized into two groups: process oriented techniques, deterministic and simulation; and data oriented techniques (DOT), regression and ANN. All techniques were used to assess productivity and cost of pile construction. Their results were compared to determine the closest assessment to real world practice. Research results show that the DOT techniques were the most appropriate whereas they had the lowest deviation from real world practice.

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References

Halpin, D. W., and Riggs, L. S. (1992). Planning and analysis of construction operations, Wiley, New York.
Harker, P. T., and Vargas, L. G.(1987). “The theory of ratio scale estimation: Saaty analytic hierarchy process.” J. Manage. Sci., 33(11), 1383–1403.
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. (1996). Applied linear statistical models, IRWIN, McGraw-Hill, New York.
Saaty, T. L. (1980). The analytic hierarchy process, McGraw-Hill, New York.
Zayed, T. M. (2001). “Assessment of productivity for concrete bored pile construction.” PhD Thesis, School of Civil Engineering, Purdue University, West Lafayette, Ind.
Zayed, T. M., and Halpin, D. W. (2001a). “Construction productivity assessment using artificial intelligence.” Canadian Society for Civil Engineering (CSCE) Conf., Victoria, B.C., Canada, C55.
Zayed, T. M., and Halpin, D. W. (2001b). “Simulation of bored piles construction.” Winter Simulation Conf., Arlington, Va.
Zayed, T. M., and Halpin, D. W. (2002a). “Concrete bored piles construction productivity index.” Construction in the 21st Century Conf., Miami, 815–822.
Zayed, T. M., and Halpin, D. W. (2002b). “Concrete bored pile construction productivity assessment using regression analysis.” Canadian Society for Civil Engineering (CSCE) Conf., 30th, Montréal.

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Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 130Issue 4August 2004
Pages: 490 - 499

History

Received: May 30, 2002
Accepted: Jun 9, 2003
Published online: Jul 15, 2004
Published in print: Aug 2004

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Authors

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Tarek M. Zayed
Assistant Professor, in Construction Engineering and Management, Zagazig Univ., Zagazig, Egypt; presently, Assistant Professor, Dept. of Building, Civil & Environmental Engineering, Concordia Univ., BE-357, 1257 Guy St., Montréal PQ, Canada H3H 1H5.
Daniel W. Halpin
Head of Division of Construction Engineering and Management, School of Civil Engineering, Purdue Univ., West Lafayette, IN 47907-1294.

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