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Chan, A P C, Wong, F K W, Chan, D W M, Yam, M C H, Kwok, A W K, Lam, E W M and Cheung, E (2008) Work at Height Fatalities in the Repair, Maintenance, Alteration, and Addition Works. Journal of Construction Engineering and Management, 134(07), 527–35.

Damnjanovic, I and Zhang, Z (2008) Risk-Based Model for Valuation of Performance-Specified Pavement Maintenance Contracts. Journal of Construction Engineering and Management, 134(07), 492–500.

Eastman, C M and Sacks, R (2008) Relative Productivity in the AEC Industries in the United States for On-Site and Off-Site Activities. Journal of Construction Engineering and Management, 134(07), 517–26.

Goedert, J D and Meadati, P (2008) Integrating Construction Process Documentation into Building Information Modeling. Journal of Construction Engineering and Management, 134(07), 509–16.

Hyun, C, Cho, K, Koo, K, Hong, T and Moon, H (2008) Effect of Delivery Methods on Design Performance in Multifamily Housing Projects. Journal of Construction Engineering and Management, 134(07), 468–82.

Nguyen, L D and Ibbs, W (2008) FLORA: New Forensic Schedule Analysis Technique. Journal of Construction Engineering and Management, 134(07), 483–91.

Salem, O and Mohanty, S (2008) Project Management Practices and Information Technology Research. Journal of Construction Engineering and Management, 134(07), 501–8.

Sanad, H M, Ammar, M A and Ibrahim, M E (2008) Optimal Construction Site Layout Considering Safety and Environmental Aspects. Journal of Construction Engineering and Management, 134(07), 536–44.

Tam, V W Y, Le, K N and Le, H N (2008) Using Gaussian and Hyperbolic Distributions for Quality Improvement in Construction: Case Study Approach. Journal of Construction Engineering and Management, 134(07), 555–61.

  • Type: Journal Article
  • Keywords: Quality control; Construction management; Gaussian process; Case reports;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2008)134:7(555)
  • Abstract:
    The Gaussian distribution and the 6σ principle have been widely used in the field of construction quality management with great success. This paper proposes a theoretical study on a new hyperbolic distribution using the 6σ principle to improve quality in construction management. The hyperbolic and Gaussian distributions are then numerically compared by estimating their important statistical properties, such as population in range, number of defects, yield percentage, and defects per million opportunities. The impacts of these factors are briefly discussed to give guidance to organizations in the construction industry on how to lower cost and improve project quality by prevention. A case study showing the cost data of a construction consultant company is presented. The data’s population in range and defects per million opportunities are estimated using Gaussian and hyperbolic distributions. In this particular case study, the hyperbolic distribution is shown to be more effective in quality improvement by prevention than the Gaussian distribution. This also validates the hyperbolic distribution as a suitable distribution for construction quality management.

Tang, W, Qiang, M, Duffield, C F, Young, D M and Lu, Y (2008) Incentives in the Chinese Construction Industry. Journal of Construction Engineering and Management, 134(07), 457–67.

Zhang, H, Li, H and Lu, M (2008) Modeling Time-Constraints in Construction Operations through Simulation. Journal of Construction Engineering and Management, 134(07), 545–54.