Abstract | ||
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A fuzzy reasoning algorithm was developed and implemented via an expert system to evaluate and assess the likelihood of equipment failure mode precipitation and aggravation. The scheme is based upon the fuzzification of the effects of precipitating factors provoking the failure. It consists of a fuzzy mathematical formulation which linearly relates the presence of factors catalogued as critical , important or related to the incidence of machine failure modes. This fuzzy algorithm was created to enable the inference mechanism of a constructed knowledge-based system to screen industrial equipment failures according to their likelihood of occurrence. |
Year | DOI | Venue |
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2001 | 10.1016/S0165-0114(00)00051-8 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
fuzzy relation,equipment reliability,approximate reasoning,failure mode screening,fuzzy scheme,expert systems,failure mode,knowledge based system,expert system | Data mining,Failure mode and effects analysis,Inference,Fuzzy logic,Expert system,Fuzzy set,Machine failure,Artificial intelligence,Industrial equipment,Adaptive neuro fuzzy inference system,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
121 | 3 | Fuzzy Sets and Systems |
Citations | PageRank | References |
5 | 0.71 | 0 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Daniel J Fonseca | 1 | 69 | 8.63 |
Gerald M. Knapp | 2 | 55 | 7.35 |