Estimating Project Completion Time with Monte Carlo Simulation

Authors

  • A. Fadjar Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Jl. Soekarno-Hatta Km 9, Palu 94118, Indonesia
  • N. Nirmalawati Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Jl. Soekarno-Hatta Km 9, Palu 94118, Indonesia
  • N. Hidayat Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Jl. Soekarno-Hatta Km 9, Palu 94118, Indonesia

DOI:

https://doi.org/10.22487/renstra.v3i2.448

Keywords:

Monte Carlo simulation, project scheduling, critical path method, precedence diagram method

Abstract

Risk and uncertainty are factors that construction project managers have been increasingly had to deal with. Project completion time is one of the areas where the expected time is often underestimated or shorter than the actual completion time. Monte Carlo simulation is a widely used simulation technique in modeling a process that is difficult to predict due to its random variables. This study provides a practical way to use Monte Carlo simulation to simulate a project using functions available in a spreadsheet application. A project with five activities was simulated 2000 times using minimum, maximum, and expected duration. The mean, mode, and median simulation results were then plugged into their respective precedence diagram networks to compare them. The precedence diagram computations found that mean, mode, and median project completion times were longer than the initially expected completion time. The mean, mode, and median were 50, 53, and 48 days, respectively, which were 8, 11, and 6 days longer, respectively, than the 42 days initially expected. The study showed that the Monte Carlo simulation could assist the project manager in planning a project schedule that deals with risk and uncertainty more realistically.

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Published

2022-08-31

How to Cite

Fadjar, A., Nirmalawati, N., & Hidayat, N. (2022). Estimating Project Completion Time with Monte Carlo Simulation. REKONSTRUKSI TADULAKO: Civil Engineering Journal on Research and Development, 3(2), 21-26. https://doi.org/10.22487/renstra.v3i2.448

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Articles