Towards a knowledge-based design support environment for design automation and performance evaluation.

Persistent Link:
http://hdl.handle.net/10150/184804
Title:
Towards a knowledge-based design support environment for design automation and performance evaluation.
Author:
Hu, Jhyfang.
Issue Date:
1989
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The increasing complexity of systems has made the design task extremely difficult without the help of an expert's knowledge. The major goal of this dissertation is to develop an intelligent software shell, termed the Knowledge-Based Design Support Environment (KBDSE), to facilitate multi-level system design and performance evaluation. KBDSE employs the technique, termed Knowledge Acquisition based on Representation (KAR), for acquiring design knowledge. With KAR, the acquired knowledge is automatically verified and transformed into a hierarchical, entity-based representation scheme, called the Frame and Rule Associated System Entity Structure (FRASES). To increase the efficiency of design reasoning, a Weight-Oriented FRASES Inference Engine (WOFIE) was developed. WOFIE supports different design methodologies (i.e., top-down, bottom-up, and hybrid) and derives all possible alternative design models parallelly. By appropriately setting up the priority of a specialization node, WOFIE is capable of emulating the design reasoning process conducted by a human expert. Design verification is accomplished by computer simulation. To facilitate performance analysis, experimental frames reflecting design objectives are automatically constructed. This automation allows the design model to be verified under various simulation circumstances without wasting labor in programming math-intensive models. Finally, the best design model is recommended by applying Multi-Criteria Decision Making (MCDM) methods on simulation results. Generally speaking, KBDSE offers designers of complex systems a mixed-level design and performance evaluation; knowledge-based design synthesis; lower cost and faster simulation; and multi-criteria design analysis. As with most expert systems, the goal of KBDSE is not to replace the human designers but to serve as an intelligent tool to increase design productivity.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Engineering design.; Artificial intelligence.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical and Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Rozenblit, Jerzy W.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleTowards a knowledge-based design support environment for design automation and performance evaluation.en_US
dc.creatorHu, Jhyfang.en_US
dc.contributor.authorHu, Jhyfang.en_US
dc.date.issued1989en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe increasing complexity of systems has made the design task extremely difficult without the help of an expert's knowledge. The major goal of this dissertation is to develop an intelligent software shell, termed the Knowledge-Based Design Support Environment (KBDSE), to facilitate multi-level system design and performance evaluation. KBDSE employs the technique, termed Knowledge Acquisition based on Representation (KAR), for acquiring design knowledge. With KAR, the acquired knowledge is automatically verified and transformed into a hierarchical, entity-based representation scheme, called the Frame and Rule Associated System Entity Structure (FRASES). To increase the efficiency of design reasoning, a Weight-Oriented FRASES Inference Engine (WOFIE) was developed. WOFIE supports different design methodologies (i.e., top-down, bottom-up, and hybrid) and derives all possible alternative design models parallelly. By appropriately setting up the priority of a specialization node, WOFIE is capable of emulating the design reasoning process conducted by a human expert. Design verification is accomplished by computer simulation. To facilitate performance analysis, experimental frames reflecting design objectives are automatically constructed. This automation allows the design model to be verified under various simulation circumstances without wasting labor in programming math-intensive models. Finally, the best design model is recommended by applying Multi-Criteria Decision Making (MCDM) methods on simulation results. Generally speaking, KBDSE offers designers of complex systems a mixed-level design and performance evaluation; knowledge-based design synthesis; lower cost and faster simulation; and multi-criteria design analysis. As with most expert systems, the goal of KBDSE is not to replace the human designers but to serve as an intelligent tool to increase design productivity.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectEngineering design.en_US
dc.subjectArtificial intelligence.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorRozenblit, Jerzy W.en_US
dc.contributor.committeememberZeigler, Bernard P.en_US
dc.contributor.committeememberMartinez, Ralphen_US
dc.identifier.proquest9003485en_US
dc.identifier.oclc703263176en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.