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Knowledge-based support for management of concurrent, multidisciplinary design

Published online by Cambridge University Press:  27 February 2009

Raymond E. Levitt ,
Yan Jin  and
Clive L. Dym
Raymond E. Levitt
Affiliation:
Center for Integrated Facility Engineering, Stanford University, Stanford, CA, U.S.A.
Yan Jin
Affiliation:
Civil Engingeering Department, Stanford University, Stanford, CA, U.S.A.
Clive L. Dym
Affiliation:
Department of Engineering, Harvey Mudd College, Claremont, CA, U.S.A.
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Abstract

Artificial intelligence (AI) applications to design have tended to focus on modeling and automating aspects of single discipline design tasks. Relatively little attention has thus far been devoted to representing the kinds of design ‘metaknowledge’ needed to manage the important interface issues that arise in concurrent design, that is, multidisciplinary design decision-making. This paper provides a view of the process and management of concurrent design and evaluates the potential of two AI approaches—blackboard architectures and co-operative distributed problem-solving (CDPS)—to model and support the concurrent design of complex artifacts. A discussion of the process of multidisciplinary design highlights elements of both sequential and concurrent design decision-making. We identify several kinds of design metaknowledge used by expert managers to: partition the design task for efficient execution by specialists; set appropriate levels of design conservatism for key subsystem specifications; evaluate, limit and selectively communicate design changes across discipline boundaries; and control the sequence and timing of the key (highly constrained and constraining) design decisions for a given type of artifact. We explore the extent to which blackboard and CDPS architectures can provide valid models of and potential decision support for concurrent design by (1) representing design management metaknowledge, and (2) using it to enhance both horizontal (interdisciplinary) and vertical (project life cycle) integration among product design, manufacturing and operations specialists.

Information

Type
Research Article
Information
AI EDAM , Volume 5 , Issue 2 , May 1991 , pp. 77 - 95
Copyright
Copyright © Cambridge University Press 1991

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