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Topic Id:

ID topic:	464
Partner Email:	L.J.M.Rothkrantz@tudelft.nl
Project Title:	Lifecycle simulation using Baysian calculation
Abstract:	This thesis covers the Life Cycle Simulation in the Process Industry. It covers two main areas: 1) apply the Bayesian approach for assessing the degradation of equipment of process plants and derive applicable knowledge from the results; and 2) develop a data model that facilitates the intake of diverse data from different sources: the process applications with which the chemical processes are designed and projected as a prior expectation and the real time process management and ERP-applications that provide the details with which prior estimates can be checked, thus providing the outcome of the Bayesian assessment. As a result, an application has been designed, that incorporates the different aspects of the thesis.The thesis then highlights the way the interface is used to derive helpful conclusions to the user of the simulation. The principles on how data should be provided are discussed and it is explained how this guidance is applied for this particular interface. In this part, it is as well illustrated that the usefulness of the application is enhanced by abstracting knowledge from the Bayesian calculations; and it is visualized how to provide this as a consult to the end-user. In the final part of the thesis, the effectiveness of the Bayes approach in the specific plant setting, a process that is run at the University of Delft as a test-bed, is analyzed.
Advisor:	Leon Rothkrantz
Link:
Degree:	Master
Keywords:
Computer Software
Algorithms & problem solving
Artificial intelligence & Neural networks
Data mining