Using Gaussian and hyperbolic distributions for quality improvement in construction: Case study approach

The Gaussian distribution and the 6 sigma 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 6 sigma 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.