Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-26T07:46:08.652Z Has data issue: false hasContentIssue false
  • English
  • Français

Component selection using temporal truth maintenance

Published online by Cambridge University Press:  27 February 2009

Andrew Seddon  and
Pearl Brereton
Andrew Seddon
Affiliation:
Computer Science Department, University of Keele, Keele, Staffordshire, ST5 5BG, United Kingdom
Pearl Brereton
Affiliation:
Computer Science Department, University of Keele, Keele, Staffordshire, ST5 5BG, United Kingdom
Get access Rights & Permissions [Opens in a new window]

Abstract

The application of truth maintenance techniques to the component selection phase of the engineering design process is described. The aims of the research include the selection of components that most closely match a set of requirements which include fluid characteristics, economic constraints, and company policies or preferences. In addition, we consider the storage and retrieval of requirement sets and corresponding component selections. The benefits of maintaining temporal knowledge are twofold: to enhance performance through reuse when new requirement sets are similar to previous sets, and to re-assess selections in the light of changes over time, for example, to the set of available components, to company policy, or, perhaps, to national safety regulations.

We propose a temporal truth maintenance system (TTMS) to support this management of selection knowledge over time.

Keywords

truth maintenancenonmonotonic reasoningknowledge reuseengineering design
Type
Research Article
Information
AI EDAM , Volume 8 , Issue 1 , Winter 1994 , pp. 13 - 25
Copyright
Copyright © Cambridge University Press 1994

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

BSi (1991). BS 7405: Guidelines to the Selection and Application of Flowmeters for the Measurement of Fluid Flow in Closed Circuits. British Standards Institution, Milton Keynes.Google Scholar
de Kleer, J. (1986). An assumption-based TMS. Art. Intell. 28, 127–162.CrossRefGoogle Scholar
DIN (1969). DIN 1952: Flow Measurement with Standard Nozzles, Orifice Plates and Venturi-Nozzles (in Germany). Deutschen Normenausschusses, Berlin.Google Scholar
Doyle, J. (1979). A truth maintenance system. Art. Intell. 12(3), 231–272.CrossRefGoogle Scholar
Howe, D.R. 1989. Data Analysis for Data Base Design, 2nd ed. Edward Arnold, London.Google Scholar
ISO (1973). ISO Standard 2186: Fluid Flow in Closed Conduits—Connections for Pressure Signal Transmissions Between Primary and Secondary Elements. International Standards Organisation.Google Scholar
Jacobsen, G. & Payne, B. (1989). Solving difficult real world problems with an expert system development tool using a truth maintenance system. S. African J. Sci. 85(4), 234–237.Google Scholar
Rich, E. (1983). Artificial Intelligence. McGraw-Hill Book Company, Singapore.Google Scholar
Seddon, A.P. (1991). Ph.d. thesis proposal. Working Document SRG/AS/WD9, University of Keele, Keele, United Kingdom.Google Scholar
Seddon, A.P. (1992). Conceptual model for flowmeters. Tech. Rep. TR92–11, University of Keele, Keele, United Kingdom.Google Scholar