A Knowledge Discovery in Databases (KDD) approach for extracting causes of iterations in Engineering Change Orders

Fatos Elezi, Armin Sharafi, Alexander Mirson, Petra Wolf, Helmut Krcmar, Udo Lindemann

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

7 Scopus citations

Abstract

This paper describes an implementation of a Knowledge Discovery in Databases (KDD) process for extracting the causes of iterations in Engineering Change Orders (ECOs). A data set of approximately 53,000 historical Engineering Change Orders (ECOs) was used for this purpose. Initially, the impact of iterations in ECO lead time and uncertainty is assessed. Subsequently, a semi-automatic text-mining process is employed to classify the causes of iterations. As a result, cost and technical categories of causes were identified as the main reasons for the occurrence of iterations. The study concludes that applying KDD in historic ECO data can help in identifying the causes of iterations of ECO which subsequently can provide a framework for companies to reduce these iterations. In addition, the case represents an example of benefits that can be achieved with the application of KDD in engineering change management.

Original languageEnglish
Title of host publicationASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011
Pages1401-1410
Number of pages10
EditionPARTS A AND B
DOIs
StatePublished - 2011
EventASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011 - Washington, DC, United States
Duration: 28 Aug 201131 Aug 2011

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
NumberPARTS A AND B
Volume2

Conference

ConferenceASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011
Country/TerritoryUnited States
CityWashington, DC
Period28/08/1131/08/11

Keywords

  • Engineering change management
  • Engineering change orders
  • Knowledge Discovery in Databases

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