An Ontology to Support Semantic Management of FMEA Knowledge

  • Zobia Rehman Lucian Blaga University of Sibiu, Romania COMSATS Institute of Information Technology, Abbottabad, Pakistan
  • Claudiu Vasile Kifor Faculty of Engineering and Management, Lucian Blaga University of Sibiu, Romania

Abstract

Risk mitigation has always been a special concern for organization’s strategic management. Various tools and techniques have been developed to manage risk in an effective way. Failure Mode and Effects Analysis (FMEA) is one of the tools used for effective assessment of risk. It analyzes all potential failure modes, their causes, and effects on a product or process. Moreover it recommends actions to mitigate failures in order to enhance product reliability. Organizations spend their resources and domain experts make their efforts to complete this analysis. It further helps organizations identify the expected risks and plan strategies in advance to tackle them. But unfortunately the analysis produced after spending a lot of organizational assets and experts’ struggles, is not reusable due to its natural language text based description. Information and communication technology experts proposed some solutions but they are associated with some deficiencies. Authors in [13] proposed an ontology based solution to extract and reuse FMEA knowledge from the textual documents, and this article is the first step towards its implementation. In this article we proposed our ontology for Process Failure Mode and Effects Analysis (PFMEA) for automotive domain, along with its implementation, reasoning, and data retrieval through it.

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Published
2016-07-03
How to Cite
REHMAN, Zobia; KIFOR, Claudiu Vasile. An Ontology to Support Semantic Management of FMEA Knowledge. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 11, n. 4, p. 507-521, july 2016. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1674>. Date accessed: 25 jan. 2021. doi: https://doi.org/10.15837/ijccc.2016.4.1674.

Keywords

Ontology, FMEA, Knowledge Management, OWL, Protégé, SPARQL