Siddall (engineering, McMaster Univ., Hamilton, Ontario) argues that engineers are perfectly capable of writing their own expert system computer programs, drawing on their pre-existing knowledge of languages such as FORTRAN and PASCAL, their expertise of the engineering method, their experience with

Expert system technology is receiving increasing popularity and acceptance in the engineering community. This is due to the fact that there actually exists a close match between the capabilities of the current generation expert systems and the requirements of engineering practice. Prepared by a distinguished team of experts, this book provides a balanced state-of-the-art presentation of the design principles of engineering expert systems, and a representative picture of their capabilities to assist efficiently the design, diagnosis and operation of complex industrial plants. Among the application areas covered are the following: hardware synthesis, industrial plant layout design, fault diagnosis, process control, image analysis, computer communication, electric power systems, intelligent control, robotics, and manufacturing systems. The book is appropriate for the researcher and the professional. The researcher can save considerable time in searching the scattered technical information on engineering expert systems. The professional can have readily available a rich set of guidelines and techniques that are applicable to a wide class of engineering domains.

This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment. Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering. Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.

Expert Systems for Engineering Design presents the application of expert system methods to a variety of engineering design problems. This book provides the technical details on how the methods are used to solve specific design problems in chemical engineering, civil engineering, and several others. Organized into 12 chapters, this book begins with an overview of the synthesis, the creation, and development of alternative designs. This text then examines the nature of design expertise and the types of computer tools that can enhance the expert's decision-making. Other chapters consider the integration of tools into intelligent, cooperative frameworks. This book discusses as well the use of graphic interfaces with built-in knowledge about the designs being configured. The final chapter deals with the development of software tools for automatic design synthesis and evaluation within the integrated framework of a computer-aided mechanical design system known as CASE, which stands for computer-aided simultaneous engineering. This book is a valuable resource for engineers and architects.

The goal of the International Workshop on Expert Systems in Engineering is to stimulate the flow of information between researchers working on theoretical and applied research topics in this area. It puts special emphasis on new technologies relevant to industrial engineering expert systems, such as model-based diagnosis, qualitative reasoning, planning, and design, and to the conditions in which they operate, in real time, with database support. The workshop is especially relevant for engineering environments like CIM (computer integrated manufacturing) and process automation.

Expert Systems in Construction and Structural Engineering is a valuable reference both for researchers interested in the state-of-the-art of civil engineering expert systems, and practitioners interested in exploring the practical applications of this new technology.

This monograph on integrated computer systems is one in a series of monographs published by the Expert Systems on Artificial Intelligence Committee of the ASCE Technical Council on Computer Practices. The purpose of the monograph series is to address issues in the use of expert system technology in civil engineering problem solving. Many of the publications and tools available to implement expert systems are generalized environments. The application of these environments is best achieved with an understanding of how others have succeeded or failed in using them to solve problems in the civil engineering domain. ,EM>Expert Systems for Civil Engineers: Integration Issues, broadens the scope of the monograph series from a focus on expert systems to a more general use of Artificial Intelligence (AI) techniques. The scope is also broadened by considering integration of computer programs more generally, rather than only on combining expert systems with other packages. The reason for expanding the scope of the series is to consider the role of AI in civil engineering computer environments rather than being limited to the implementation of expert systems. This follows a general trend in research and practice, to find the right tool for the problem being addressed, rather than to a priori assume an expert system approach. This report specifically describes the technical and pragmatic issues in developing integrated or distributed computer systems in which AI techniques are used and how these issues were resolved in civil engineering research and practice.

This book is written for software engineers, software project leaders, and software managers who would like to introduce a new advanced software technology, expert systems, into their product. Expert system technology brings into programming a new dimension in which "rule of thumb" or heuristic expert knowledge is encoded in the program. In contrast to conventional procedural languages {e. g. , Fortran or C}, expert systems employ high-level programming languages {Le. , expert system shells} that enable us to capture the judgmental knowledge of experts such as geologists, doctors, lawyers, bankers, or insurance underwriters. Past expert systems have been more successfully applied in the problem areas of analysis and synthesis where the boundary of lo;nowledge is well defined and where experts are available and can be identified. Early successful applications include diagnosis systems such as MYCIN, geological systems such as PROSPECTOR, or design/configu ration systems such as XC ON. These early expert systems were mainly applicable to scientific and engineering problems, which are not theoreti cally well understood in terms of decisionmaking processes by their experts and which therefore require judgmental assessment. The more recent expert systems are being applied to sophisticated synthesis problems that involve a large number of choices, such as how the elements are to be compared. These problems normally entailed a large search space and slower speed for the expert systems designed. Examples of these systems include factory scheduling applications such as ISIS, or legal reasoning applications such as TAXMAN.

EXPERT SYSTEMS, KNOWLEDGE ENGINEERING FOR HUMAN REPLICATION. An expert system is a computer program that attempts to replicate the expertise and decision-making abilities of a human expert. Expert systems are the most widely developed area of artificial intelligence, with a variety of applications ranging from medical diagnosis through to financial decision-making and geological prospecting. They often use a heuristic or self-learning approach to the solution of a problem, in which feedback of the results of a particular course of action influences subsequent decisions. Expert systems usually have two principal parts: a knowledge base (a special database, which contains facts and other information representing the rules and experience of an expert practitioner in a particular field); and an inference engine, which interprets the knowledge base in relation to the particular problem being presented.

This book presents the Proceedings of the Tenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, focusing on the theoretical aspects of intelligent systems research as well as extensions of theory of intelligent thinking machines.