Modeling construction labour productivity using fuzzy logic and exploring the use of fuzzy hybrid techniques

Recent trends indicate that fuzzy techniques (fuzzy set theory, fuzzy logic, and fuzzy hybrid models) have found increased application in the construction domain, even more so in the last half decade. This paper presents the application of fuzzy expert models and fuzzy hybrid concepts in modeling construction labour productivity, which is critical information for scheduling and estimating construction projects. The fuzzy expert model addresses both subjective and objective factors affecting labour productivity of two common industrial construction processes: rigging and welding pipe. The resulting model matched highly with respect to linguistic terms; however, the numerical match was low, indicating the need to have fuzzy hybrid models to improve the predictive ability of the fuzzy expert model. Further research is underway to combine the strengths of fuzzy logic in addressing subjective and linguistic evaluations of labourer performance with the strengths of other artificial intelligence methods, such as neural networks, in training and calibrating the fuzzy model to properly address the context variables, as well as the principal variables.