Abstract
The problem of optimal allocation of resources in limited circumstances to handle assigned tasks has been dealt with in a wide variety of research fields. Various research methodologies have been proposed to address uncertainties such as waiting and waste in construction projects, but they do not take into account the complexity of construction production systems. In this study, a research approach was proposed that simplified the construction production system into a work package to be serviced and a work group to provide services. In addition, a conceptual 4D digital twin framework considering the uncertainty of the construction production system was proposed. This framework includes BIM as an information model and a queuing model as a decision-making model. Through case projects, we have presented how this framework can be used for decision making in several statuses. As a result of the analysis using the performance index of the queuing model, it was possible to monitor the status of the system according to the allocation of resources. In addition, it was possible to confirm the improvement of the performance index according to the additional arrangement of the work group and the activity cycle of the work package. The framework presented in this study helps to quantitatively analyze the state of the system according to the input data based on empirical knowledge, but it has a limitation in that it cannot present an optimized resource allocation solution. Therefore, in future research, it is necessary to consider the grafting of machine learning technology that can provide optimal solutions by solving complex decision-making problems.
Highlights
Large-scale construction projects always involve uncertainty and risk
Predicting when a customer work package will arrive in a queuing system is highly uncertain because, as previously analyzed, due to the characteristics of the apartment construction project, the work on the preceding work package may take very long or very short compared to the 7-day activity cycle
The queueing model was used as a research approach to simplify the complex construction production system
Summary
Large-scale construction projects always involve uncertainty and risk. there is a need to quantitatively analyze the construction production system to minimize uncertainty and risk. The input of human resources in a construction project is based on a contract between a general contractor who manages the project and subcontractors who perform various processes. 5D simulation research suggests a framework for decision making in the financial part of a construction project [9], and there are studies exploring the functions of 5D CAD in terms of process management [10]. BIM provides valuable information to project managers in a unit process or decision-making situation at a specific point in time, but it does not express the degree of uncertainty and risk such as waiting or waste in the production system. This study intends to propose a digital twin framework for optimal decision-making support that can minimize subcontractor waiting or waste by the convergence of management science methodologies that can predict probabilistically
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