Developing an expert system of failure analysis

Yeong Ho Ho, Huei Sen Wang, Hei Chia Wang

研究成果: Conference contribution

摘要

An Equipment Failure Analysis Expert System (EFAES) is to be developed to help the engineers diagnose the causes of the failure mechanism and provide a reliable remedy. This system is based on an innovative reasoning approach: integrating the rule-based reasoning (RBR) and the case-based reasoning (CBR) methods The architecture developed in the system consists of six major elements-"Factor and Attribute Editor", Knowledge Actuation Interface", "Knowledge Base", "User Interface", "Inference Engine" and "Explanation Facility". Here, the RBR system consists of 46 failure mechanisms and their rules. The CBR system consists of 586 failure cases which are coded and composed from 23 factors and their 265 attributes. Also, this system provides a variety of inference methods which allows retrieving the best answers to users. For the RBR system, performance is directly check the inferred order of the document ranking list. For the CBR system, the effectiveness of each inference method is evaluated by using "Recall", "Precision", and "F-Measure" approaches. From the test results, many recommendations are proposed.

原文English
主出版物標題Innovation for Applied Science and Technology
頁面2375-2379
頁數5
DOIs
出版狀態Published - 2013 二月 20
事件2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012 - Kaohsiung, Taiwan
持續時間: 2012 十一月 22012 十一月 6

出版系列

名字Applied Mechanics and Materials
284-287
ISSN(列印)1660-9336
ISSN(電子)1662-7482

Other

Other2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012
國家Taiwan
城市Kaohsiung
期間12-11-0212-11-06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • 引用此

    Ho, Y. H., Wang, H. S., & Wang, H. C. (2013). Developing an expert system of failure analysis. 於 Innovation for Applied Science and Technology (頁 2375-2379). (Applied Mechanics and Materials; 卷 284-287). https://doi.org/10.4028/www.scientific.net/AMM.284-287.2375