Artificial Intelligence and Expert Systems for Engineers - Krishnamoorthy , S. Rajeev.pdf

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Artificial Intelligence and Expert Systems for Engineers
by C.S. Krishnamoorthy; S. Rajeev
CRC Press, CRC Press LLC
ISBN:
0849391253
Pub Date:
08/01/96
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Preface
Title
Chapter 1—Introduction
1.1 General
1.2 Developments in Artificial Intelligence
1.3 Developments in Expert Systems
1.4 Role of AI and Expert Systems in Engineering
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Chapter 2—Search Techniques
2.1 Introduction
2.2 Problem Definition and Solution Process
2.3 Production Systems
2.4 Search Techniques
2.4.1 Breadth-First Search
2.4.2 Depth-First Search
2.4.3 Heuristic Search
2.4.4 Generate and Test
2.4.5 Best-First Search
2.4.6 Agenda-Driven Search
2.5 Problem Decomposition and
AND-OR
Graphs
Chapter 3—Knowledge-Based Expert System
3.1 Introduction
3.2 What is KBES?
3.3 Architecture of KBES
3.3.1 Knowledge Base
3.3.2 Inference Mechanisms
3.3.3 Inexact Reasoning
3.3.4 Non-Monotonic Reasoning
3.3.5 Reasoning Based on Certainty Factors
Chapter 4—Engineering Design Synthesis
4.1 Introduction
4.2 Synthesis
4.3 Decomposition Model for Synthesis
4.4 Role of a Synthesiser in KBES Environment
4.5 An Architecture for a Synthesiser - A Generic Tool
4.6 Generic Synthesis Tool - GENSYNT
4.6.1 Application Examples
Chapter 5—Criticism and Evaluation
5.1 Introduction
5.2 Methodologies Used in a Knowledge-Based Environment
5.3 A Framework for Critiquing and Evaluation
5.3.1 Knowledge Representation Framework
5.3.2 Inference Mechanism
5.3.3 Algorithm for Overall Rating of a Hierarchical Solution
5.4 Generic Critiquing Tool - Gencrit
5.4.1 Critiquing Knowledge Base in GENCRIT
5.4.2 Working of GENCRIT
Chapter 6—Case-Based Reasoning
6.1 Introduction
6.2 Applications of Case-Based Reasoning
6.2.1 Planning
6.2.2 Design
6.2.3 Diagnosis
6.3 Case-Based Reasoning Process
6.3.1 Case Retrieval
6.3.1.1 Selection by search conditions
6.3.1.2 Classification by relevance
6.3.1.3 Classification by performance
6.3.1.4 Illustration of the case retrieval process
6.3.2 Solution Transformation
6.3.2.1 Problem detection
6.3.2.2 Focusing on appropriate parts
6.3.2.3 Solution transformation
6.3.2.4 Evaluation and testing
6.3.3 Case Storing
6.4 A Framework for CBR in Engineering Design (CASETOOL)
6.4.1 Case Retrieval
6.4.2 Solution Transformation
6.4.3 Case Storing
6.5 Architecture of CASETOOL
6.6 Application Example
6.6.1 Architecture of VASTU
6.6.2 CBR Process in VASTU
Chapter 7—Process Models and Knowledge-Based Systems
7.1 Introduction
7.2 Expert Systems for Diagnosis
7.2.1 Understanding of Domain Knowledge
7.2.2 Evolution of Knowledge Nets
7.2.3 Transformation of Knowledge from Nets to Rule Base
7.3 Blackboard Model of Problem Solving
7.3.1 Blackboard Architecture
7.3.2 Blackboard Framework
7.3.3 Integrated Engineering System
7.3.4 Illustrative Example
7.4 ODESSY - An Integrated System for Preliminary Design of Reinforced Concrete
Multistory Office Buildings
7.4.1 Task Analysis of Building Design
7.4.2 Synthesis-Criticism-Modification Model
7.4.3 Layout Planning
7.4.4 Conceptual and Preliminary Design
7.4.5 Architecture of ODESSY
7.5 Conceptual Design of a Car Body Shape
7.5.1 Functional Requirements
7.5.2 Design Parameters
7.5.3 Design Decoupling
7.5.4 Synthesis and Critiquing of Solutions
7.5.5 Case-Based Evaluation of Shapes
7.6 SETHU - An Integrated KBES for Concrete Road Bridge Design
7.6.1 Task Analysis of Bridge Design Process
7.6.2 Process Model
7.6.3 KBES Development Tool
7.6.4 SETHU: Architecture
7.7 Future Trends
7.7.1 Genetic Algorithms
7.7.2 Artificial Neural Networks
7.7.3 Concurrent Engineering
Appendix A
Appendix B
Appendix C
Index
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Artificial Intelligence and Expert Systems for Engineers
by C.S. Krishnamoorthy; S. Rajeev
CRC Press, CRC Press LLC
ISBN:
0849391253
Pub Date:
08/01/96
Search Tips
Advanced Search
Search this book:
Table of Contents
Title
Preface
The book is aimed at bringing out a comprehensive presentation of Artificial Intelligence (AI) based
methodologies and software tools wherein, for the first time, the focus is on addressing a wide spectrum of
problems in engineering.
Expert system methodology has been applied in the past to a number of problems of planning, design,
diagnostics etc. However, the problems of engineering design have not been adequately addressed, since these
problems have to be addressed in an integrated manner with knowledge from different domains and sources.
Continued research in the last ten years has recently resulted in the emergence of new methodologies which
will enable building of automated integrated design systems that will have the ability to handle the entire
design process. These methodologies include design synthesis, design critiquing, case-based reasoning etc.,
leading to concurrent engineering. Details of these methodologies and tools are at present available only in the
form of technical papers and reports of research projects that have been carried out in academic and other
institutions.
Many research and development projects have been carried out by the authors in the past few years, and
prototype systems have been developed for specific applications to engineering systems. During this process,
the authors have proposed generic frameworks and have developed efficient software tools to meet the
requirements of engineering design. This intensive work, coupled with the teaching of a graduate course on
Computer-Aided Design, motivated the authors to write a book on the subject with descriptions of different
methods and a presentation of software tools that meet the requirements of integrated knowledge-based
systems in engineering. The authors hope that the book will serve as a textbook for students and teachers, and
the software frameworks and tools will provide the requisite resource material to researchers and
professionals who are interested in developing knowledge-based systems in various disciplines of
engineering.
The book is divided into seven chapters. The first chapter presents an overview of the developments in the
areas of AI and Knowledge-Based Expert System (KBES) applications to engineering. The relevance and
importance of the use of AI-based methodologies for solving engineering problems are well brought out in
this chapter.
The predominant component of any AI-based program is in the extensive use of search techniques. Depending
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