Interactive engineering systems design: A study for artificial intelligence applications

Abstract To develop KBSs as designer's assistants requires a detailed understanding of the process of design. We describe engineering systems design as a feedback process that suffers from several sources of uncertainty and complexity. Because of the broad range of design methodologies available, the need to classify design approaches, based on the amount of analytical information available to the designer, is argued. Three classes of design technique: analytical, procedural and experimental are identified and characterized. A detailed model of the procedural design process is developed and the importance of redesign is emphasized. Procedural design is a symbiotic process, the designer working closely with a computer. To establish which parts of the design should be performed by the designer and which by the machine, their respective information processing capabilities are examined. The designer works in terms of a conceptual framework and performs calculations using the machine's manipulative framework. He receives design assistance from a machine resident knowledge framework.

[1]  John McDermott Domain Knowledge and the Design Process , 1981, DAC 1981.

[2]  Donald Michie Technology Lecture: The superarticulacy phenomenon in the context of software manufacture , 1986, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[3]  Paul R. Cohen,et al.  An Architecture for Application of Artificial Intelligence to Design , 1984, 21st Design Automation Conference Proceedings.

[4]  Y. Hung,et al.  Multivariable Feedback: A Quasi-Classical Approach , 1982 .

[5]  Kristian J. Hammond,et al.  Explaining and Repairing Plans that Fail , 1987, IJCAI.

[6]  Sanjay Mittal,et al.  A Knowledge-Based Framework for Design , 1986, AAAI.

[7]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[8]  David Christopher Brown Expert systems for design problem-solving using design refinement with plan selection and redesign , 1984 .

[9]  J.H. Taylor,et al.  An expert system architecture for computer-aided control engineering , 1984, Proceedings of the IEEE.

[10]  B. Chandrasekaran,et al.  Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design , 1986, IEEE Expert.

[11]  Tom M. Mitchell,et al.  An Intelligent Aid for Circuit Redesign , 1983, AAAI.

[12]  Clive L. Dym,et al.  PRIDE: An Expert System for the Design of Paper Handling Systems , 1986, Computer.

[13]  G. Stein,et al.  Multivariable feedback design: Concepts for a classical/modern synthesis , 1981 .

[14]  M.J. Denham Design issues for CACSD systems , 1984, Proceedings of the IEEE.

[15]  B. Kouvaritakis,et al.  A design technique for linear multivariable feedback systems , 1977 .

[16]  W. Y. Ng Application of optimization-based methods in control system design , 1988 .

[17]  B. Francis,et al.  A Course in H Control Theory , 1987 .

[18]  David C. Brown,et al.  Knowledge and Control for a Mechanical Design Expert System , 1986, Computer.

[19]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[20]  J. Ackermann,et al.  Future design environments for control engineering , 1987, Autom..

[21]  H. H. Rosenbrock,et al.  Computer Aided Control System Design , 1974, IEEE Transactions on Systems, Man, and Cybernetics.