A framework for integrating process monitoring, diagnosis and supervisory control
Process operations management deals with tasks that are executed to operate a process plant safely and economically. These tasks can be classified as data acquisition, regulatory control, monitoring, fault diagnosis, supervisory control, scheduling and planning. While these operational tasks may be intrinsically different from each other, they are, however, closely related to each other and can not be treated as isolated tasks. Hence, there exists a clear need for an integrated framework so that the operational decision-making can be made more comprehensively and effectively. While such an integrated approach is very compelling and desirable, achieving it is no simple task as there are many challenges in realizing integration. This thesis attempts to provide an integrated solution strategy to the process operations management problem. The tasks considered here are: monitoring, diagnosis, data reconciliation and supervisory control. To this end, a core set of solution strategies are developed that can handle the individual problems in a consistent manner with the idea of integration in the background. Also, explorations are made into the conceptual integration of different solution tasks themselves. The concepts are validated through various chemical engineering case studies. ^
Major Professor: V. Venkatasubramanian, Purdue University.
Engineering, Chemical|Psychology, Industrial|Operations Research
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