Rainfall is a major source of uncertainty in outdoor operations, which can significantly impact the duration of tasks and the overall scheduling of projects. This concern greatly affects building construction projects, where the activity usually involves concrete and steel-related activities. This study proposed RainPlan, a simulation system that incorporates rainfall data to estimate the duration needed for the activity to finish for building construction projects. RainPlan incorporates historical precipitation records and uses Monte Carlo Simulation to generate the rain value, fuzzy techniques that relate to categorizing the level of rain, and experts’ opinions regarding the impact of rain on the activities. RainPlan’s response will be evaluated with two different case studies, which are a two-story house project and a storage warehouse project. Both of these case studies results will be compared against traditional scheduling methods, which don’t take rain into account. The result shows that rain has quite a significant impact that may lead to disaster
delays. A further analysis is also conducted where the project starting time is changed and the city is changed. Different starting times will affect the duration needed to complete the project; a different city will generate a completely different result from other cities since each city has its own historical precipitation record. Our finding suggests that incorporating rain-informed duration estimation into building construction scheduling simulations can lead to more robust and efficient project scheduling, particularly in outdoor operations that are sensitive to weather conditions. RainPlan offers a valuable tool for project managers to improve scheduling accuracy and optimize project outcomes.

Rainfall is a major source of uncertainty in outdoor operations, which can significantly impact the duration of tasks and the overall scheduling of projects. This concern greatly affects building construction projects, where the activity usually involves concrete and steel-related activities. This study proposed RainPlan, a simulation system that incorporates rainfall data to estimate the duration needed for the activity to finish for building construction projects. RainPlan incorporates historical precipitation records and uses Monte Carlo Simulation to generate the rain value, fuzzy techniques that relate to categorizing the level of rain, and experts’ opinions regarding the impact of rain on the activities. RainPlan’s response will be evaluated with two different case studies, which are a two-story house project and a storage warehouse project. Both of these case studies results will be compared against traditional scheduling methods, which don’t take rain into account. The result shows that rain has quite a significant impact that may lead to disaster
delays. A further analysis is also conducted where the project starting time is changed and the city is changed. Different starting times will affect the duration needed to complete the project; a different city will generate a completely different result from other cities since each city has its own historical precipitation record. Our finding suggests that incorporating rain-informed duration estimation into building construction scheduling simulations can lead to more robust and efficient project scheduling, particularly in outdoor operations that are sensitive to weather conditions. RainPlan offers a valuable tool for project managers to improve scheduling accuracy and optimize project outcomes.

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