Conference Proceedings

Fifth International Conference on Advances in Computing, Communication and Information Technology - CCIT 2017

Management of Project Schedule Exceptions based on Bayesian Networks



The market size of plant projects in overseas is so large that domestic EPC project contractors are actively seek ing the overseas projects and then trying to meet completion plans since successful fulfillment of these projects can provide great opportunities for them to expand into new foreign markets. International EPC projects involve all of the uncertainties commo n to domestic projects as well as uncertainties specific to foreign projects including marine transportation, customs, regulations, nationality, culture and so on. When overseas project gets off - schedule, the resulting uncertainty may trigger unexpected ex ceptions and then critical effects to the project performance. It usually require much more time and costs to encounter these exceptions in foreign sites compared to domestic project sites. Therefore, an exception handling approach is required to manage ex ceptions effectively for successful project progress in foreign project sites. In this research, we proposed a methodology for prediction and evaluation of exceptions caused by risks in international EPC projects based on sensitivity analysis and Bayesian Networks. First, we identified project schedule risks and related exceptions, which may meet during the fulfillment of foreign EPC projects that is performed in a sequence of engineering, procurement, preparatory manufacture, foreign shipping, constructio n, inspection and modification activities, and affect project performance, using literature review and expert interviews. The impact of exceptions to the schedule delay were also identified. Second, we proposed a methodology to predict the occurrence of ex ceptions caused by project risks and evaluate them. Using sensitivity analysis, we can identify activities that critically affect schedule delay and need to focus by priority. Then, we use Bayesian Networks to predict and evaluate exceptions. Third, we app lied the proposed methodology to an international EPC project example to validate the proposed approach. Finally, we concluded the research with the further research topics. We expect that the proposed approach can be extended to apply in exception managem ent in project management .

Conference Title : Fifth International Conference on Advances in Computing, Communication and Information Technology - CCIT 2017
Conference Date(s) : 02-03 September, 2017
Place : Novotel Zurich City-West Schiffbaustrasse 13, 8005 Zurich, Switzerland
No fo Author(s) : 4
DOI : 10.15224/978-1-63248-131-3-24
Page(s) : 82
Electronic ISBN : 978-1-63248-131-3
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