An Integrated Framework for Quantifying and Alleviating the Impact of Workspace Congestion on Learning-Based Construction Schedules

Abstract

One of the most fundamental contemporary issues in the construction industry is the improvement of labor productivity. Among the factors affecting labor productivity is the learning curve which proved to be a major contributor to enhancing production rates on projects of repetitive nature in particular. Nonetheless, this does not reflect real construction practices whereby various activity conditions, work circumstances, crew morale, and other influencing factors can negatively impact the learning curve of workers, and in turn their productivity. This has thereby led to studying factors affecting the learning curve in varying degrees, of which workspace congestion proved from literature to be of paramount importance. However, none of the previous research efforts has studied the impact of workspace congestion on labor productivity through the learning curve effect. Additionally, limited effort was carried out to quantify losses or any perceived decline in labor productivity due to site congestion and, as a result, resolve the scheduling repercussions. In order to address the aforementioned limitations, this research aims at effectively studying and analyzing how workspace congestion affects the learning curve of workers on projects of repetitive nature, and in turn their productivity and project schedule performance and how this workspace congestion can be minimized. Therefore the objective behind this study is three-fold: (1) Investigating the various factors affecting the learning curve and highlighting the impact of the congestion factor in particular, (2) Quantifying the impact of congestion on the learning curve of laborers and consequently the overall linear project schedule by devising a generic mathematical function and an agent-based behavioral model, and (3) Eliminating or alleviating potential congestions and improving the performance of learning-based linear schedules by developing a space-time optimization framework. Several experiments were conducted and results highlighted the potential of the proposed integrated framework in alleviating construction workspace congestion, and improving labor productivity and project schedule performance.