1. Objectives:
The project focuses on process control and has two objectives:
• to develop an approach that allows plant integration, i.e., where information about the process at one stage in the plant is used to improve process control in another part of the plant. Material goes through the plant, and information from earlier stages of processes can be helpful in selecting processing strategies for later stages.
• the approach must allow the integration of processing stages with different types of sensors and controls, e.g., the integration of a mining stage with a refining stage.
• the approach must allow for intelligent path planning, for different types of feedstocks, and for different environments, including equipment failures and variations in the processing environment.
2. The technological problems & risks:
This type of application is a reasonable candidate for the application of AI and expert system technology, especially since information poor mining stages are meant to provide input for information rich refining stages. An integration of qualitative and quantitative information is needed. Existing expert system technology has to be adapted to allow for better representation of time and pattern recognition windows sliding over time. The main objective is to adapt the technology to be able to provide a functionally satisfactory and cost effective solution to the problems.
3. Personnel:
Much of the development is done by Rainer von Königslöw acting as consultant, under contract to Syncrude Research, which in turn is doing the applied research for the main operating unit.
4. Project status & plans:
A special facility supporting the development and testing of an expert system for predictive process control was developed. The facility was utilized for developing pilot prototypes of an expert system for predicting upsets in centrifugal extractors, and for providing advice to operators. The expert system is being developed by Syncrude Research and integrated into the plant process control system.