A case study of failure mode analysis with text mining methods

Chen, Lin & Nayak, Richi (2007) A case study of failure mode analysis with text mining methods. In Ong, K.-L., Li, W., & Gao, J. (Eds.) 2nd International Workshop on Integrating Artificial Intelligence and Data Mining (AIDM 2007), 2 December 2007, Gold Coast, Qld..

View at publisher


The maintenance dataset provided by SunWater contains information about failed assets also known as components and their corresponding failure modes. Currently, extraction of this information from the dataset been conducted in a manual manner, which is very tedious, time consuming and cumbersome work. It is necessary to discover an automatic method to decide/extract the failure mode. This paper presents three methods that were attempted in an effort to solve this problem. The performance of each method is analysed in detail and suggestions for how the outcomes can be improved are also proposed.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

286 since deposited on 31 Jul 2008
25 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 14249
Item Type: Conference Paper
Refereed: Yes
ISBN: 9781920682651
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2007 Australian Computer Society
Copyright Statement: Copyright © 2007, Australian Computer Society, Inc. This
paper appeared at the Second Workshop on Integrating AI and
Data Mining (AIDM 2007), Gold Coast, Australia.
Conferences in Research and Practice in Information
Technology (CRPIT), Vol. 84, Kok-Leong Ong, Junbin Gao
and Wenyuan Li, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included.
Deposited On: 31 Jul 2008 00:00
Last Modified: 29 Feb 2012 13:33

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page