On using the Gaussian and hyperbolic distributions to improve quality in construction

Tam, V W Y and Le, K N (2008) On using the Gaussian and hyperbolic distributions to improve quality in construction. Journal of Engineering, Design and Technology, 6(2), pp. 112-123. ISSN 1726-0531

Abstract

Purpose: Various method have been used by organisations in the construction industry to improve quality, employing mainly two major techniques: management techniques such as quality control, quality assurance, total quality management; and statistical techniques such as cost of quality, customer satisfaction and the six sigma principle. The purpose of this paper is to show that it is possible to employ the six sigma principle in the field of construction management provided that sufficient information on a particular population is obtained. Design/methodology/approach: Statistical properties of the hyperbolic distribution are given and quality factors such as population in range, number of defects, yield percentage and defects per million opportunities are estimated. Graphical illustrations of the hyperbolic and Gaussian distributions are also given. From that, detailed comparisons of these two distributions are numerically obtained. The impacts of these quality factors are briefly discussed to give a rough guidance to organisations in the construction industry on how to lower cost and to improve project quality by prevention. A case study on a construction project is given in which it is shown that the hyperbolic distribution is better suited to the cost data than the Gaussian distribution. Cost and quality data of all projects in the company are collected over a period of eight years. Each project may consist of a number of phases, typically spanning about three months. Each phase can be considered as a member of the project population. Quality factors of this population are estimated using the six sigma principle. Findings: The paper finds that by using a suitable distribution, it is possible to improve quality factors such as population in range, yield percentage and number of defects per million opportunities. Originality/value: This paper is of value in assessing the suitability of the hyperbolic and Gaussian distributions in modelling the population and showing that hyperbolic distribution can be more effectively used to model the cost data than the Gaussian distribution.

Item Type: Article
Uncontrolled Keywords: Gaussian distribution; probability theory; quality management; six sigma
Index terms: suitability, methodology, construction project, population, quality assurance, six sigma, total quality management, cost data, construction industry, quality management, prevention, quality control, modelling, customer satisfaction, case study
Subjects: demography, industry analysis, design criteria, quality assurance, performance measurement, research methods, accounting and finance, production management, service delivery, financial risk, project delivery, analytical methods, evaluation methods, data collection methods
Topics: Engineering Principles, Project Management, Research Practice, Cost Management, Stakeholder Management, Quality Management, Urban Studies, Design Practice
Descriptive scope: 4 PCTE

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here