Abstract
Current applications of knowledge-based expert systems in manufacturing involve decision-making that is based on information that is readily interpretable. In process control, the relationship between the underlying process behavior and the sensed information is not usually well understood. In addition, the required response speed of the system can be quite short; from a few milliseconds to a few seconds. The dual requirements for fast decisions and the incorporation of “fuzzy” knowledge requires new approaches to the development of expert systems for process control. Both advanced, fast executing artificial intelligence algorithms and improved, fundamental physical understanding of the underlying manufacturing processes that are being controlled are necessary. It is important to emphasize that neither the artificial intelligence nor the manufacturing engineering communities currently have the tools and techniques that are required to solve the full range of process control problems. It is essential that communication and cooperation between the two disciplines be increased to give a full appreciation for the current strengths and limitations of the respective science bases and to define a clear direction for advanced, fundamental research within each discipline.
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