Abstract
This paper reports the development of an approach to integrate the appropriate modeling techniques for estimating the effect of project quality management (PQM) on construction performance. This modeling approach features a causal structure that depicts the interaction among the PQM factors affecting quality performance in a given construction operation. In addition, it makes use of fuzzy sets and fuzzy logic in order to incorporate the subjectivity and uncertainty implicit in the performance assessment of these PQM factors to discrete-event simulation models. The outcome is a simulation approach that allows experimenting with different performance levels of the PQM practices implemented in a construction project and obtaining the corresponding productivity estimates of the construction operations. These estimates are intended to facilitate the decision making regarding the improvement of a PQM system implemented in a construction project. A case study is used to demonstrate the usefulness of the proposed simulation approach for evaluating diverse performance improvement alternatives for a PQM system.
Highlights
Since the endeavor reported in this paper focuses on the construction operational level, Deming’s thinking gives meaning to the convention of using, for the purposes of this modeling approach, interruptions, low productivity periods, and reworks for measuring quality performance and representing the effect of project quality management (PQM) on the productivity of construction activities
The intention is to support decision making concerning the improvement of PQM systems and the increase of project performance
The proposed simulation-based approach is based on the analysis of the factors involved in the relationship between the PQM practices and the performance of construction activities: the performance levels of the PQM practices to determine the quality levels of the project requirements, and these quality levels will determine the amount of disruptions that eventually will affect the productivity of construction operations
Summary
Discrete-event simulation has been proven to be an effective technique to deal with the uncertainty involved in the planning of construction projects [1]; project planning processes, such as scheduling [1,2,3,4], cost estimating [5, 6], risk management [7], safety management [8, 9], lean construction analysis [10,11,12,13], constructability review [14], construction logistics analysis [15,16,17], contractor selection [18], and productivity estimation [19,20,21], among other efforts, have been addressed using this technique. Several simulation models have been proposed to estimate and improve the productivity of construction operations such as pile construction [19, 22], steel fabrication [21, 23], drainage maintenance [10], pavement construction [24, 25], pipe fabrication [13, 14], pipeline construction [26], bridge construction [27, 28], concrete production [29], high-rise structural work [30], construction of concrete structures [31], and tunnel construction [32,33,34], among several others All these models have included the effect of a number of factors affecting the productivity of these construction operations— such as weather conditions, labor experience, contractor experience, equipment condition, site conditions, and several others—they have had limited consideration of, or even overlooked, the effect of quality performance.
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