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A Forecasting and Decision Model that Incorporates Accident Risks  

Yang Hee-Joong (Department of Industrial and Information Systems Engineering, Chongju University)
Lee Keun-Boo (Department of Industrial and Information Systems Engineering, Chongju University)
Oh Se-Ho (Department of Industrial and Information Systems Engineering, Chongju University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.27, no.4, 2004 , pp. 1-6 More about this Journal
Abstract
For a given plant design, improved decisions on when to shutdown an existing plant may be obtained by making better predictions of failure rates, by exerting efforts to collect more relevant information or by improving decision making models which put that information to best use. It is important that the models include the value of possible loss of lives and fear along with cleanup, decommissioning, relocation if the decisions derived from the model are to be useful. The decision model we have described enables us to investigate a class of optimal decisions on whether to shutdown or continue operating one period of time. The analysis and decision process is repeated at the end of each period with additional information about new costs and risks.
Keywords
bayesian decision; forecasting; safety systems;
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