Improving data quality in DSM modelling: A structural comparison approach

Steffen F-Schmitz, David C. Wynn*, Wieland Biedermann, P. John Clarkson, Udo Lindemann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.

Original languageEnglish
Title of host publicationICED 11 - 18th International Conference on Engineering Design - Impacting Society Through Engineering Design
Pages369-380
Number of pages12
StatePublished - 2011
Externally publishedYes

Publication series

NameICED 11 - 18th International Conference on Engineering Design - Impacting Society Through Engineering Design
Volume4

Keywords

  • Design structure matrix
  • Knowledge elicitation
  • Structural similarity

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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