Framework for developing labour-hour prediction models from project design features: case study in structural steel fabrication

Assigning labour-hours to a certain scope of work during design and estimating is still more of an art than a science. This research proposes a data-driven approach that uses multiple linear regression (MLR) and available historical data from building information models (BIM) to associate project labour-hours and project design features. The framework relies on an enhanced version of stepwise regression technique to select the most relevant predictive factors and generate a predictive model without compromising the achievable accuracy of regression. The framework also encompasses analytical methods for justifying MLR application, validating the resulting model, and establishing range estimates for point-value predictions. In collaboration with an industry partner, the framework application is exemplified by analyzing labour-hours and design features for structural steel fabrication, leading to the creation of a valid MLR model in the simplest form. Finally, pros and cons for the proposed framework and opportunities for future research are discussed.