IJCATR Volume 2 Issue 3

Risk Prediction for Production of an Enterprise

Kumar Ravi Sheopujan Singh
10.7753/IJCATR0203.1006
keywords : Bayesian network, UnBBayes, MEBN, PR-OWL.

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Despite all preventive measures, there is so much possibility of risks in any project development as well as in enterprise management. There is no any standard mechanism or methodology available to assess the risks in any project or production management. Using some precautionary steps, the manager can only avoid the risks as much as he can. To address this issue, this paper presents a probabilistic risk assessment model for the production of an enterprise. For this, Multi-Entity Bayesian Network (MEBN) has been used to represent the requirements for production management as well as to assess the risks adherence in production management, where MEBN combines expressivity of first-order logic and probabilistic feature of Bayesian network. Bayesian network provides the feature to represent the probabilistic uncertainty and reasoning about probabilistic knowledge base, which is used here to represent the probable risks behind each causes of a risk. The proposed probabilistic model is discussed with the help of a case study, which is used to predict risks inherent in the production of an enterprise, which depends upon various measures like labour availability, power backup, transport availability etc.
@artical{k232013ijcatr02031006,
Title = "Risk Prediction for Production of an Enterprise",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "2",
Issue ="3",
Pages ="237 - 244",
Year = "2013",
Authors ="Kumar Ravi Sheopujan Singh"}
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