A DHM-ABM Framework for Construction Task Assignment Based on Workers' Physiological Capabilities

Abstract

The construction industry has been constantly facing evolving and growing challenges and suffering from time delays and cost overruns. One key component of construction projects consists of labor productivity and its influencing factors such as ergonomics. In fact, applying ergonomics and understanding the interactions among workers and their assigned tasks have shown a decrease in workers’ discomfort, a positive impact on productivity, a reduction in project costs, and an increase in value creation. As such, several studies have been conducted in an attempt to properly assign construction tasks and optimize the performance of crews. Some studies have only measured physiological capabilities, while other studies have linked the mental workload with the workers’ mental capabilities. However, no study has yet been carried out to estimate physiological task workload and match it with the corresponding workers’ capabilities. Incorporating recent contributions from the fields of Digital Human Modeling (DHM) and Agent-Based Modeling (ABM), this research study develops an integrated framework for proactive performance control of construction crews through studying different task assignment techniques. More specifically, DHM is adopted to model different construction activities and generate physiological task demands, then ABM is used to map modeled tasks to construction workers and obtain performance values in terms of productivity and safety. A validation survey was administered among site engineers, and results highlighted the practicality and feasibility of the proposed hybrid framework and its potential in efficiently matching tasks with workers based on their physiological capabilities. The proposed system is sought to highly benefit contractors by helping them measure their workers’ strengths and then optimally assign them to the right tasks.