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Artificial intelligence in process engineering
74
BOOK REVIEWS
the image data contains errors which distort the consistency conditions which must be met if the actual shape of a polyhedron is to be described. This chapter proposes a scheme of optimisation, which allows a consistent object shape to be constructed from inconsistent data, by solving a set of linear equations. The proposed technique is applied to the problem of shape from motion, and to 3-D recovery based on the rectangularity hypothesis and parallelism hypothesis. An appendix, titled "Fundamentals of group theory", gives readers a brief review of the mathematics used in the book. The author lays emphasis on the theorem known as Schur's Lemma, which plays a central role in group representation theory. Some basic concepts related to topologies, Mansfield and Lie groups, Lie algebras and spherical harmonics are introduced. In general, the text is well-written, and presents an advanced mathematical tool for the interpretation and understanding of images. The material demonstrates that abstract mathematical concepts can be of enormous help in building intelligent computer-vision systems. The extensive references provided greatly broaden the scope of the whole text. Despite the lack of practical engineering applications, the theory and new methods proposed show great potential for extending image-understanding techniques. All these factors distinguish the book from others published in this field, and add to its value for electrical engineers, in proposing an analytical approach to problem-solving in visual scene understanding. The book is recommended to anyone interested in a theoretical approach to the discipline of machine vision. YUAN BAO-ZONG Northern Jiaotong University, P.R. C.
Artificial Intelligence in Process Engineering, edited by M I C H A E L L. MAVROVOUNIOTIS. Academic Press, San Diego (1990). 367pp., $49.95, ISBN No: 0-12-480575-2.
This book provides valuable insight into the application of AI techniques to chemical or biothermal process engineering. The collection of ten topics by numerous contributors covers the domains of process diagnosis, control and design. The AI techniques used are equally wide-ranging, encompassing qualitative modelling, neural networks and expert systems. The book should appeal to both AI researchers/ practitioners and process engineers who are interested in the synthesis of artificial intelligence and process engineering. The diversity of the techniques and applications implies that the contents of each chapter should be regarded as a representative contribution rather than an exhaustive study.
In order to bridge the technology gap between the disciplines, the various authors have endeavoured to provide some introduction to the AI techniques employed, as well as some background to the problem or application. In many chapters, they have succeeded admirably. Nevertheless, some a priori knowledge in both fields greatly facilitates the understanding of the material. A large portion of the book is devoted to process fault diagnosis. The emphasis on this particular topic is justified by the fact that it is an area that is often typified by ad hoc procedures and heuristic solutions. Other areas that are also covered are process control and process design. A pervasive theme in the book is the need to combine heuristic, qualitative and quantitative knowledge in complex engineering systems. The synthesis of theoretical and empirical engineering is extremely important. Chapter 1 covers the qualitative reasoning of chemical reaction systems. In particular, the QSIM algorithm is employed for qualitative simulation. The authors describe how qualitative models of reaction systems are built. The use of partial quantitative knowledge to limit the number of possible behaviours in qualitative models is also discussed. In Chap. 2, a software tool, called CONFIG, is described which integrates qualitative and discreteevent simulation and modelling. It takes a model-based approach to system and fault diagnosis. A notable feature is its emphasis on the development of software and the formulation of procedures for failure management using the system design rather than the heuristics obtained through plant operation. A novel application of expert systems is the diagnosis of programmable logic controller operation, presented in Chap. 3. The authors argue that conventional diagnostic methods are not sufficient for complex PLC applications. They show how expert-system techniques are able to focus attention on critical areas and effectively decrease the time and effort in diagnosing dead operating states. Chapter 4 outlines fault detection and diagnosis using a neural network. The discussion is significant because it represents a sound application of neural networks and differs from many other applications in that it deals~ with continuous values, as opposed to binary or discrete values. A valuable contribution is the inclusion of experimental data and results. A model-based approach to fault diagnosis is addressed in Chap. 5. Although the basic technique of constraint propagation used is not novel, the authors have modified it to perform group propagation to minimize searching and simplify computation. The system is also able to deal with multiple faults. Chapter 6 stresses the importance of the synthesis of deep and shallow knowledge. Approximate reasoning in an expert system is used to diagnose power plant malfunctions. Considerable detail on modelling realworld processes in thermal power plants is provided. The theme in the book changes in Chap. 7 from
BOOK REVIEWS
diagnosis to expert design. An intelligent computeraided engineering tool called XIMKON is used to facilitate the design, modelling, analysis and synthesis of control systems. An important feature of this system is its interface to a large number of numerically-based tools, emphasizing the need for symbolic and numerical coupling. Chapter 8 describes an expert system for batch reactor control. The system takes the process state at each sample and diagnoses conditions which require control responses. A learning process is used to assess the performance of each batch to improve the control of subsequent batches. The design of protein purification processes is addressed in Chap. 9. While the discussion on the design domain is comprehensive, there is a lack of information regarding the AI techniques employed, other than the fact that a rule-based forward chaining inference was used. In the final chapter, an adaptive knowledge-based system for separation scheme synthesis is described. This is an interesting contribution because it uses a , wide range of AI techniques including fuzzy logic, the
75
learning mechanisms of neural networks, objectoriented databases, rules and blackboards. Several typographical errors were evident. In general, they did not adversely affect the overall readability of the book. Most of the illustrations were clear and augmented the text to good effect. However, some of them exhibited a combination of poor quality and illegibility. The index is adequate but could be more comprehensive. Every chapter concludes with a list of references and recommended literature. This will prove to be extremely useful to readers who wish to pursue a particular topic in greater detail. An analysis of the references shows that many important and formative articles have been included that either lay the theoretical foundations to a particular field or provide more-general discussion on a specific subject. In summary, the book achieves what it sets out to do and that is to provide a representative cross-section of applications of AI in process engineering. It is certainly recommended by this reviewer. VERNON LUN
University of the Witwatersrand, South Africa
BOOK REVIEWS
the image data contains errors which distort the consistency conditions which must be met if the actual shape of a polyhedron is to be described. This chapter proposes a scheme of optimisation, which allows a consistent object shape to be constructed from inconsistent data, by solving a set of linear equations. The proposed technique is applied to the problem of shape from motion, and to 3-D recovery based on the rectangularity hypothesis and parallelism hypothesis. An appendix, titled "Fundamentals of group theory", gives readers a brief review of the mathematics used in the book. The author lays emphasis on the theorem known as Schur's Lemma, which plays a central role in group representation theory. Some basic concepts related to topologies, Mansfield and Lie groups, Lie algebras and spherical harmonics are introduced. In general, the text is well-written, and presents an advanced mathematical tool for the interpretation and understanding of images. The material demonstrates that abstract mathematical concepts can be of enormous help in building intelligent computer-vision systems. The extensive references provided greatly broaden the scope of the whole text. Despite the lack of practical engineering applications, the theory and new methods proposed show great potential for extending image-understanding techniques. All these factors distinguish the book from others published in this field, and add to its value for electrical engineers, in proposing an analytical approach to problem-solving in visual scene understanding. The book is recommended to anyone interested in a theoretical approach to the discipline of machine vision. YUAN BAO-ZONG Northern Jiaotong University, P.R. C.
Artificial Intelligence in Process Engineering, edited by M I C H A E L L. MAVROVOUNIOTIS. Academic Press, San Diego (1990). 367pp., $49.95, ISBN No: 0-12-480575-2.
This book provides valuable insight into the application of AI techniques to chemical or biothermal process engineering. The collection of ten topics by numerous contributors covers the domains of process diagnosis, control and design. The AI techniques used are equally wide-ranging, encompassing qualitative modelling, neural networks and expert systems. The book should appeal to both AI researchers/ practitioners and process engineers who are interested in the synthesis of artificial intelligence and process engineering. The diversity of the techniques and applications implies that the contents of each chapter should be regarded as a representative contribution rather than an exhaustive study.
In order to bridge the technology gap between the disciplines, the various authors have endeavoured to provide some introduction to the AI techniques employed, as well as some background to the problem or application. In many chapters, they have succeeded admirably. Nevertheless, some a priori knowledge in both fields greatly facilitates the understanding of the material. A large portion of the book is devoted to process fault diagnosis. The emphasis on this particular topic is justified by the fact that it is an area that is often typified by ad hoc procedures and heuristic solutions. Other areas that are also covered are process control and process design. A pervasive theme in the book is the need to combine heuristic, qualitative and quantitative knowledge in complex engineering systems. The synthesis of theoretical and empirical engineering is extremely important. Chapter 1 covers the qualitative reasoning of chemical reaction systems. In particular, the QSIM algorithm is employed for qualitative simulation. The authors describe how qualitative models of reaction systems are built. The use of partial quantitative knowledge to limit the number of possible behaviours in qualitative models is also discussed. In Chap. 2, a software tool, called CONFIG, is described which integrates qualitative and discreteevent simulation and modelling. It takes a model-based approach to system and fault diagnosis. A notable feature is its emphasis on the development of software and the formulation of procedures for failure management using the system design rather than the heuristics obtained through plant operation. A novel application of expert systems is the diagnosis of programmable logic controller operation, presented in Chap. 3. The authors argue that conventional diagnostic methods are not sufficient for complex PLC applications. They show how expert-system techniques are able to focus attention on critical areas and effectively decrease the time and effort in diagnosing dead operating states. Chapter 4 outlines fault detection and diagnosis using a neural network. The discussion is significant because it represents a sound application of neural networks and differs from many other applications in that it deals~ with continuous values, as opposed to binary or discrete values. A valuable contribution is the inclusion of experimental data and results. A model-based approach to fault diagnosis is addressed in Chap. 5. Although the basic technique of constraint propagation used is not novel, the authors have modified it to perform group propagation to minimize searching and simplify computation. The system is also able to deal with multiple faults. Chapter 6 stresses the importance of the synthesis of deep and shallow knowledge. Approximate reasoning in an expert system is used to diagnose power plant malfunctions. Considerable detail on modelling realworld processes in thermal power plants is provided. The theme in the book changes in Chap. 7 from
BOOK REVIEWS
diagnosis to expert design. An intelligent computeraided engineering tool called XIMKON is used to facilitate the design, modelling, analysis and synthesis of control systems. An important feature of this system is its interface to a large number of numerically-based tools, emphasizing the need for symbolic and numerical coupling. Chapter 8 describes an expert system for batch reactor control. The system takes the process state at each sample and diagnoses conditions which require control responses. A learning process is used to assess the performance of each batch to improve the control of subsequent batches. The design of protein purification processes is addressed in Chap. 9. While the discussion on the design domain is comprehensive, there is a lack of information regarding the AI techniques employed, other than the fact that a rule-based forward chaining inference was used. In the final chapter, an adaptive knowledge-based system for separation scheme synthesis is described. This is an interesting contribution because it uses a , wide range of AI techniques including fuzzy logic, the
75
learning mechanisms of neural networks, objectoriented databases, rules and blackboards. Several typographical errors were evident. In general, they did not adversely affect the overall readability of the book. Most of the illustrations were clear and augmented the text to good effect. However, some of them exhibited a combination of poor quality and illegibility. The index is adequate but could be more comprehensive. Every chapter concludes with a list of references and recommended literature. This will prove to be extremely useful to readers who wish to pursue a particular topic in greater detail. An analysis of the references shows that many important and formative articles have been included that either lay the theoretical foundations to a particular field or provide more-general discussion on a specific subject. In summary, the book achieves what it sets out to do and that is to provide a representative cross-section of applications of AI in process engineering. It is certainly recommended by this reviewer. VERNON LUN
University of the Witwatersrand, South Africa