This thesis relates to the area of short term scheduling and control in batch process plants. A batch process plant consists of individual plant items linked by a pipe network through which product is routed. The structure of the network and the valve arrangements which control the routing severely constrains the availability of plant items for configuration in routes when a plant is operating. Current approaches to short term scheduling contain simplifying assumptions which ignore these constraints and this leads to unrealistic and infeasible schedules. The work undertaken investigates the use of techniques from the areas of Artificial Intelligence (AI) and Discrete Event Simulation (DES) in order to overcome these simplifying assumptions and develop good schedules which can be implemented in a plant. The main divisions of work cover a number of areas. The development of a representation scheme for batch plant networks, and procedures for reasoning about the constraints imposed by their structure to infer the actual availability of plant items for routing purposes at any time. The development of a dynamic rule-based route configuration procedure which takes into account the constraints on plant item availability. The development of an activity scheduling framework for batch plants based on this. The development of a dynamic simulation model to take account of finite capacity constraints in a batch plant. The integration of these elements in a hybrid structure to make best use of the techniques available from the areas of AI and DES. The representation scheme and procedures developed for reasoning about the constraints in a plant network enable the simplifying assumptions of other approaches to be overcome so that the system can produce good feasible schedules. The hybrid structure is a practical one to take for implementation and enables the best use of techniques from AI and DES.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:387394 |
Date | January 1993 |
Creators | Goodall, William Richard |
Publisher | University of Warwick |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://wrap.warwick.ac.uk/78612/ |
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