Efficient process monitoring and analysis tools provide the means for automated supervision and control of manufacturing plants and therefore play an important role in plant safety, process control and assurance of end product quality. The availability of a large number of different process monitoring and analysis tools for a wide range of operations has made their selection a difficult, time consuming and challenging task. Therefore, an efficient and systematic knowledge base coupled with an inference system is necessary to support the optimal selection of process monitoring and analysis tools, satisfying the process and user constraints. A knowledge base consisting of the process knowledge as well as knowledge on measurement methods and tools has been developed. An ontology has been designed for knowledge representation and management. The developed knowledge base has a dual feature. On the one hand, it facilitates the selection of proper monitoring and analysis tools for a given application or process. On the other hand, it permits the identification of potential applications for a given monitoring technique or tool. An efficient inference system based on forward as well as reverse search procedures has been developed to retrieve the data/information stored in the knowledge base.

• Technical University of Denmark (DTU)

• Oral doses
• Modeling

1. Inference system
2. Knowledge base
3. modeling
4. Ontology
5. Oral doses
6. Other
7. pat
8. Process monitoring
9. Sensor