Expert System For Process Control Research Articles

A review of: “Expert Systems in Process Control.” By JANET EFSTATHIOU. (Longman, 1989) [Pp. 178] Paperback, £40.00. Level: postgraduate/industrial researcher.

A review of: “<i>Expert Systems in Process Control.</i>” By JANET EFSTATHIOU. (Longman, 1989) [Pp. 178] Paperback, £40.00. Level: postgraduate/industrial researcher.

Process control — a challenge for expert system technology

This paper gives a small introduction on expert systems in general, followed by a discussion on the problems one encounters when building expert systems for process control and ways to deal with these problems. Finally it gives an overall structure of what an expert system for process control should consists of.

A contribution to the organization of an expert system for process control of FMC

The distributed processes control model was investigated. A discussion of the automated acquisition of knowledge for process control is presented. The logical solution concept and basic details for implementing an interpreter are described. How it functions was considered, as well as the language for the control of expressions in base rules. A set of rules from the rule base are presented to show a simplified method of organizing a knowledge base by Petri net models of robots and machines.

Automated acquisition of knowledge for an expert system for process control

Efficiency in industrial processes is extremely important. Expert systems have been used in industrial processes with resulting improvements in efficiency. Expert systems rely on rules normally acquired by a knowledge engineer. These rules comprise the knowledge of the expert system. The paper describes a system for the automated acquisition of knowledge for an expert system for process control. The distillation column is the process chosen for testing the proposed system. Results are given to demonstrate the validity of the ideas presented.

AUTO_SAFE: An expert controller for sequential and batch sequential processes

It is generally recognised that industrial processes depend heavily on sequential control. Paradoxically, this technique of control has received from control theorists, less attention than it deserves. In view of its logical basis, this class of control is an ideal candidate for rule-based expert systems. Features of one such expert system are presented in this paper, along with observations related to the development of expert systems for process control.

Some lessons learned using expert systems for process control

Two expert systems are used to monitor two industrial processes, looking for problems. The processes are an adipic acid reactor and a heat exchanger. When a problem occurs, the process operator is alerted and is told the problem and its probable cause. Expert systems have also been used to tune proportional-integral-derivative controllers and to help select flow meters to suit customer requirements. Experience with these expert systems has led to practical results and to some lessons for using expert systems for process control. The lessons form the bulk of the paper and deal with limits to expert systems, how and where expert systems fit in, knowledge-base engineering, and software engineering for expert systems.

Expert Systems Methodology for Real-time Process Control

Abstract The methodology of real-time expert systems is discussed, within the constraints of achievable paradigms and computational capabilities. Serious applications will require the representation of hundreds of objects, thousands of knowledge frames and often thousands of rapidly changing data inputs. Static expert systems based on snap-shot views of the process and pattern-matching paradigms cannot cope with such large, complex problems within current or nearterm expected computational capabilities. An expert system design for real-time problems requires the consideration of representation of temporal knowledge, efficient inference paradigm design, truth maintenance and other issues. A design appropriate for process control includes consideration of large knowledge bases, knowledge maintenance, knowledge validation, representation of deep knowledge and other issues. The authors present a survey of prior work, and a framework of specific criteria and design suggestions for real-time expert systems for process control.

Intelligent materials processing

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.

Panel Discussion: Use of Expert Systems in Process Control

Panel Discussion: Use of Expert Systems in Process Control