Table of Contents
Journal of Quality and Reliability Engineering
Volume 2014, Article ID 203427, 18 pages
Research Article

Simulation-Based Fuzzy Logic Approach to Assessing the Effect of Project Quality Management on Construction Performance

1Facultad de Ingeniería, Universidad Autónoma de Yucatán, Apartado Postal 150 Cordemex, 97111 Mérida, YUC, Mexico
2Department of Civil and Environmental Engineering, Hole School of Construction Engineering, 3-014 Markin/CNRL, NREF, University of Alberta, Edmonton, AB, Canada T6G 2W2
3Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada

Received 25 October 2013; Revised 3 April 2014; Accepted 8 April 2014; Published 7 May 2014

Academic Editor: Adiel Teixeira de Almeida

Copyright © 2014 Gilberto A. Corona-Suárez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.