Analyzing Scaffolding Needs for Industrial Construction Sites Using Historical Data

Industrial construction includes a wide range of construction projects such as petroleum refineries and chemical plants, which involve several trades such as civil, mechanical, and electrical. Different trades carry out different tasks on these projects, and often depend on scaffolds to access their work areas. Quantification of scaffold requirements of large projects is difficult due to variability in work area heights and congestion, and the multiple trades that need to be serviced by the scaffold system. Traditional estimating methods rely on percentages of direct trade hours or volume of work area and usually result in significant deviation from real scaffold costs. The study presented in this paper aims to develop better understanding and estimates of scaffold needs for industrial construction sites, based on analysis of data collected from a mega project over the course of two and a half years by a major contractor. The study seeks to discover patterns and reliable correlations that may exist between required scaffold hours and other work attributes that can allow for development of a reliable estimation model. The paper presents the results of initial analysis and exploration of data mining experiments, in addition to the challenges faced, and future research recommendations.

[1]  Gary R. Searer,et al.  Certifying That Existing Suspended Scaffold Structural Support Elements and Lifeline Anchorages Comply with Federal OSHA Requirements , 2010 .

[2]  Robert T. Ratay Temporary structures in construction operations : proceedings of a session sponsored by the Construction Division of the American Society of Civil Engineers in conjunction with the ASCE Convention in Atlantic City, New Jersey, April 29, 1987 , 1987 .

[3]  Sung Hoon An,et al.  Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning , 2004 .

[4]  Yacine Rezgui,et al.  Review of information and the state of the art of knowledge management practices in the construction industry , 2001, The Knowledge Engineering Review.

[5]  Richard L. Tucker,et al.  Is construction project planning really doing its job? A critical examination of focus, role and process , 1987 .

[6]  W. F. Chen,et al.  High clearance scaffold systems during construction —II. Structural analysis and development of design guidelines , 1996 .

[7]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[8]  Ki Sang Son,et al.  Structural Analysis of Steel Pipe Scaffolding Based on the Tightening Strength of Clamps , 2010 .

[9]  R. Stine Model Selection Using Information Theory and the MDL Principle , 2004 .

[10]  H. Murat Gunaydin,et al.  A neural network approach for early cost estimation of structural systems of buildings , 2004 .

[11]  Hojjat Adeli,et al.  Regularization neural network for construction cost estimation , 1998 .

[12]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[13]  Ian H. Witten,et al.  Induction of model trees for predicting continuous classes , 1996 .

[14]  Peter Reutemann,et al.  WEKA Manual for Version 3-6-10 , 2008 .

[15]  Robert I. Carr Cost-Estimating Principles , 1989 .

[16]  Evangelos Simoudis,et al.  An Overview of Issues in Developing Industrial Data Mining and Knowledge Discovery Applications , 1996, KDD.

[17]  J. R. Illingworth Temporary Works - Their Role in Construction , 1987 .

[18]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..

[19]  Gary R. Searer,et al.  Designing Suspended Scaffold Structural Support Elements and Lifeline Anchorages in Conformance with Federal OSHA Requirements , 2010 .

[20]  Carl E. Rasmussen,et al.  In Advances in Neural Information Processing Systems , 2011 .

[21]  Gary David Holt,et al.  Scaffolding for high-rise concrete construction: A French, German and UK comparison , 1998 .

[22]  H. Bozdogan Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions , 1987 .

[23]  Eibe Frank,et al.  WEKA Explorer User Guide for Version 3-4 , 2007 .

[24]  Dorian Pyle,et al.  Data Preparation for Data Mining , 1999 .

[25]  Chimay J. Anumba,et al.  Knowledge management in the architecture, engineering and construction industry , 2002 .

[26]  J. S. Kim,et al.  Effectiveness of OLAP-based cost data management in construction cost estimate , 2007 .

[27]  Mark Ebden Gaussian Processes for Regression: A Quick Introduction , 2008 .

[28]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[29]  D. Mackay,et al.  Introduction to Gaussian processes , 1998 .

[30]  Carlos V. Gonzalez Analysis of Industrial Construction activities using Knowledge Discovery Techniques , 2011 .