During project implementation, risk becomes an integral part of project monitoring.
Therefore. a tool that could dynamically include elements of risk in project progress monitoring is
needed. The objective of this study is to develop a general framework that addresses such a
concern. The developed framework consists of three interrelated major building blocks, namely:
Risk Register (RR), Bayesian Network (BN), and Project Time Networks (PTN) for dynamic
project monitoring. RR is used to list and to categorize identified project risks. PTN is utilized for
modeling the relationship between project activities. BN is used to reflect the interdependence
among risk factors and to bridge RR and PTN. A residential development project is chosen as a
working example and the result shows that the proposed framework has been successfully
applied. The specific model of the development project is also successfully developed and is used
to monitor the project progress. It is shown in this study that the proposed BN-based model
provides superior performance in terms of forecast accuracy compared to the extant models