The framework for an expert system to generate alternative products in concurrent engineering design

Many engineering design problems require reference to standards or codes of practice to ensure that acceptable safety and performance criteria are met. Extracting relevant data from such documents can, however, be a problem for the unfamiliar user. The use of expert systems to guide the retrieval of information from standards and codes of practice is proposed as a means of alleviating this problem. Following a brief introduction to expert system techniques, a tool developed by the authors for building expert system guides to standards and codes of practice is described. The steps involved in encoding the knowledge contained in an arbitrarily chosen standard are illustrated. Finally, a typical consultation illustrates the use of the expert system guide to the standard.

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AGENTS for cooperating expert systems in concurrent engineering design

Artificial intelligence for engineering design analysis and manufacturing ◽

10.1017/s0890060400000858 ◽

1993 ◽

Vol 7 (3) ◽

pp. 145-158 ◽

Cited By ~ 3

Author(s):

Guo Q. Huang ◽

John A. Brandon

Keyword(s):

Expert Systems ◽

Engineering Design ◽

Concurrent Engineering ◽

General Purpose ◽

Main Theme ◽

Computer Tools ◽

System A ◽

And Control ◽

Domain Independent

A main theme of concurrent engineering is the effective communication between relevant disciplines. Any computer tools for concurrent engineering must provide sufficient constructs and strategies for this purpose. This paper describes the AGENTS system, a domain-independent general-purpose Object-Oriented Prolog language for cooperating expert systems in concurrent engineering design. Emphasis is placed on demonstrating the use of the AGENTS constructs for distributed knowledge representation and the cooperation strategies for communication, collaboration, conflict resolution, and control. A simple case study is presented to illustrate the balance between simplicity and flexibility.

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Qualitative Evaluation of Engineering Designs Using Fuzzy Logic

Volume 3: 22nd Design Automation Conference ◽

10.1115/96-detc/dac-1449 ◽

1996 ◽

Author(s):

Rajkumar Roy ◽

Ian C. Parmee ◽

Graham Purchase

Keyword(s):

Decision Support ◽

Expert System ◽

Engineering Design ◽

Evaluation System ◽

Design Space ◽

Qualitative Evaluation ◽

Fuzzy Rules ◽

Design Solution ◽

Fuzzy Expert System ◽

Adaptive Search

Abstract The paper describes a Qualitative Evaluation System developed using a fuzzy expert system. The evaluation system gives a qualitative rating to design solutions by considering manufacturability aspects, choice of materials and some special preferences. The information is used in decision support for engineering design. The system is an integrated part of a decision support tool for engineering design called the ‘Adaptive Search Manager’ (ASM). ASM uses an adaptive search technique to identify multiple design solutions for a 12 dimensional Turbine Blade Cooling System design problem. Thus the task has been to develop a fuzzy expert system that can qualitatively evaluate any design solution from a design space using a realistically small number of fuzzy rules. The developed system utilises a knowledge separation and then a knowledge integration technique. The design knowledge is first separated into three categories: inter variable knowledge, intra variable knowledge and heuristics. Inter variable knowledge and intra variable knowledge are integrated using a concept of “compromise”. The qualitative evaluation system can evaluate any design solution within the 12 dimensional design space, but uses only 44 fuzzy rules and one function that implements the inter variable knowledge.

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The Complementary Roles of Symbolic Computing and Numerical Optimization in Engineering Design Software

13th Design Automation Conference: Volume 1 — Design Methods, Computer Graphics, and Expert Systems ◽

10.1115/detc1987-0010 ◽

1987 ◽

Author(s):

R. Ellsworth ◽

A. Parkinson ◽

F. Cain

Keyword(s):

Expert System ◽

Engineering Design ◽

Numerical Optimization ◽

Optimization Methods ◽

Design Rule ◽

Rule Base ◽

Design Problems ◽

Symbolic Computing ◽

Engineering Design Problems ◽

Trial And Error Method

Abstract In many engineering design problems, the designer converges upon a good design by iteratively evaluating a mathematical model of the design problem. The trial-and-error method used by the designer to converge upon a solution may be complex and difficult to capture in an expert system. It is suggested that in many cases, the design rule base could be made significantly smaller and more maintainable by using numerical optimization methods to identify the best design. The expert system is then used to define the optimization problem and interpret the solution, as well as to apply the true heuristics to the problem. An example of such an expert system is presented for the design of a valve anti-cavitation device. Because of the capabilities provided by the optimization software, the expert system has been able to outperform the expert in the test cases evaluated so far.

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Building an Expert System for Engineering Design Based on the Object-Oriented Knowledge Representation Concept

14th Design Automation Conference ◽

10.1115/detc1988-0037 ◽

1988 ◽

Author(s):

S. Akagi ◽

K. Fujita

Keyword(s):

Expert System ◽

Knowledge Representation ◽

Engineering Design ◽

Design Process ◽

Model Building ◽

Object Oriented ◽

Design Model ◽

Design Problems ◽

Design Variables ◽

Effective Diagnosis

Abstract An expert system is developed for engineering design based on object-oriented knowledge representation concept. The design process is understood as determining design variables and their relationships which compose design model. The design model is represented as a network in the computer system using the object-oriented knowledge representation. The system built with the above concept provides the following abilities: 1) flexible model building and easy modification, 2) effective diagnosis of the design process, 3) supporting method for redesign, 4) a hybrid function with numerical computations and graphics, and 5) applicability for various design problems. Finally, it is applied to the basic design of a ship.

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