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..
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 countsare sourced monthly fromand 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 theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays 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.
|Item Type:||Conference Paper|
|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|
|Last Modified:||29 Feb 2012 23:33|
Repository Staff Only: item control page