کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10323329 | 660933 | 2005 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid expert system for equipment failure analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This paper outlines the development of a web-based expert system, equipment failure analysis expert system (EFAES), for the largest steel company in Taiwan. The EFAES inference engine employs both case-based reasoning (CBR) and rule-based reasoning (RBR) to generate a hybrid recommendation list for cross validation. Moreover, this inference engine was designed to support a hierarchical multi-attribute structure. Unlike the traditional 'flat' attribute structure, this hierarchical multi-attribute structure allows experts to weigh the attributes dynamically. Two two-dimensional matrixes, multi-attribute analysis (MAA) and subattributes matrix (SAM), are used to store the attributes' weight values. Normalized relative spending (NRS) is adapted to normalize the weight values for the inference engine. The system recommends both cases and rules, which can give more information in recognizing the failure types. According to our experimental results, applying our proposed method in an inference engine to analyze failure can result in better quality recommendations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 28, Issue 4, May 2005, Pages 615-622
Journal: Expert Systems with Applications - Volume 28, Issue 4, May 2005, Pages 615-622
نویسندگان
Hei-Chia Wang, Huei-Sen Wang,