Bayesian-based Project Monitoring: Framework Development and Model Testing

Authors

  • Budi Hartono Industrial Engineering Program, Mechanical and Industrial Engineering Department, Universitas Gadjah Mada Jl. Grafika 2, Yogyakarta
  • Riesa Ayuningtyas Industrial Engineering Program, Mechanical and Industrial Engineering Department, Universitas Gadjah Mada Jl. Grafika 2, Yogyakarta
  • Yun Prihantina Mulyani Industrial Engineering Program, Mechanical and Industrial Engineering Department, Universitas Gadjah Mada Jl. Grafika 2, Yogyakarta

:

https://doi.org/10.9744/jti.17.2.61-70

Keywords:

Bayesian Networks, Risk Register, Risk Factors, Project Monitoring

Abstract

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. This 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.

Author Biography

Budi Hartono, Industrial Engineering Program, Mechanical and Industrial Engineering Department, Universitas Gadjah Mada Jl. Grafika 2, Yogyakarta

Budi is an assistant professor with research interest in project management, systems engineering and complexity analysis. He is currently the director of Project Management Institute Indonesia Chapter, Yogyakarta Branch.

References

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Ayuningtyas, R., and Hartono, B., Project Monitoring using Bayesian Networks: Framework and Model, Paper presented at the 5th AUN/SEED-net Regional Conference on Manufacturing Engineering & the 1st Human Factors and Ergonomics Society of the Philippines Conference, De LaSalle University, Manila, Philippines, 2013

Gardoni, P., Reinschmidt, K.F., and Kumar, R., A Probabilistic Framework for Bayesian Adaptive Forecasting of Project Progress, Zachry Department of Civil Engineering, Texas A&M University, USA, 2007.

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Vandervoorde, S., amd Vanhoucke, M., A Comparison of Different Project Duration Forecasting Methods Using Earned Value Metrics, International Journal of Project Management, 24, 2006, pp. 289-302.

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Published

2016-10-03

How to Cite

[1]
B. Hartono, R. Ayuningtyas, and Y. P. Mulyani, “Bayesian-based Project Monitoring: Framework Development and Model Testing”, Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 17, no. 2, pp. 61-70, Oct. 2016.

Issue

Vol. 17 No. 2 (2015): DECEMBER 2015

Section

Articles

License

Articles published in the Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License (CC BY).


This work is licensed under a  Creative Commons Attribution License (CC BY).