2019
DOI: 10.1007/s10845-019-01466-z
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A data-driven approach for constructing the component-failure mode matrix for FMEA

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Cited by 39 publications
(13 citation statements)
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“…However, before addressing the standardization of all FMEA cells, we noticed cases of merged cells, which we address in part of this paper. Similar to [12], we opted for a data-driven approach that requires limited labeling effort.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…However, before addressing the standardization of all FMEA cells, we noticed cases of merged cells, which we address in part of this paper. Similar to [12], we opted for a data-driven approach that requires limited labeling effort.…”
Section: Methodsmentioning
confidence: 99%
“…Such solutions are labor-intensive and time-consuming. As such, text mining algorithms are proposed to extract a list of frequent failure modes and build the standard failure mode vocabulary (e.g., the method proposed in [12]).…”
Section: Introductionmentioning
confidence: 99%
“…A critical step in FMEA is identifying potential failure modes for product sub-systems, components, and processes, for which component-failure mode knowledge is necessarily needed as an important source of knowledge. Reference [10] proposes a method to construct the component-failure mode matrix automatically by mining unstructured and short quality problem texts and mapping as well as representing them as component-failure knowledge. Reference [11] proposed a data-driven approach and a system design based on the approach for decision-making on equipment maintenance.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Duan et al [28] analyze evaluations of failure modes in natural language by FMEA experts, using fuzzy sets to extract features, and the kmeans algorithm to cluster the failure modes. Xu et al [29] proposed a method to construct the component-failure mode (CF) matrix automatically, by mining unstructured texts using the Apriori algorithm and the semantic dictionary WordNet to build a standard set of failure modes. As in the work by Arunajadai et al [26], the matrix is used for grouping the failure modes using clustering algorithms, such as the K-means.…”
Section: Related Workmentioning
confidence: 99%