Probabilistic Risk Assessment of the Shipyard Industry using the Bayesian Method
Corresponding email: mintobasuki@yahoo.co.id
Published at : 27 Jan 2014
Volume : IJtech
Vol 5, No 1 (2014)
DOI : https://doi.org/10.14716/ijtech.v5i1.157
Basuki, M., Manfaat, D., Nugroho, S., Dinariyana, A., 2014. Probabilistic Risk Assessment of the Shipyard Industry using the Bayesian Method. International Journal of Technology. Volume 5(1), pp. 88-97
| Minto Basuki | Department of Shipbuilding Engineering, Faculty of Mineral and Marine Engineering, Institut Teknologi Adhi Tama Surabaya, Jalan Arief Rachman Hakim 100, Surabaya, Indonesia |
| Djauhar Manfaat | Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember Surabaya, Kampus ITS Sukolilo, Surabaya, Indonesia |
| Setyo Nugroho | Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember Surabaya, Kampus ITS Sukolilo, Surabaya, Indonesia |
| AAB Dinariyana | Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember Surabaya, Kampus ITS Sukolilo, Surabaya, Indonesia |
The shipbuilding industry is characterized by high-risk business activities; therefore, caution should be taken in its operational processes. From upstream to downstream, the shipbuilding industry depends on other industries. In this study, a risk assessment was conducted on the construction of new vessels using the Bayesian network approach; accordingly, the risk assessment was carried out using a probabilistic value at risk (VaR). The study was carried out by PT PAL Indonesia in association with the construction of a new tanker ship (building production codes M271 and M272). An analysis was conducted on three main components of new vessel construction—design components, material and production components, and sub-components of the previous two components. From the study, we could conclude that the probability of delay for new vessel construction caused by design delay is 0.05; the probability of delay caused by material delay is 0.65; and the probability of delay caused by production delay is 0.3. For delays caused by design factors, a yard plan is the sub-component that contributes predominantly to delays (i.e., probability of 0.3). For delays caused by material factors, the sub-component with the greatest impact is hull and machinery outfitting, with a probability of 0.3. For delays caused by production factors, the sub-component with the biggest impact is hull construction, with a probability of 0.39. Thus, we could conclude that a project delay would occur if the material component and the hull construction sub-components were not handled properly.
Bayesian network, probability, shipyard industry
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