A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis

  • Zobia Rehman 1. Faculty of Engineering and Management Lucian Blaga University of Sibiu, Romania 2. Department of Computer Science Comsats Institute of Information Technology, Pakistan
  • Stefania Kifor Lucian Blaga University of Sibiu, Romania

Abstract

Failure Mode and Effects Analysis (FMEA) is a systematic method forprocedure analyses and risk assessment. It is a structured way to identify potentialfailure modes of a product or process, probability of their occurrence, and their overalleffects. The basic purpose of this analysis is to mitigate the risk and the impactassociated to a failure by planning and prioritizing actions to make a product or aprocess robust to failure. Effective manufacturing and improved quality productsare the fruits of successful implementation of FMEA. During this activity valuableknowledge is generated which turns into product or process quality and efficiency. Ifthis knowledge can be shared and reused then it would be helpful in early identificationof failure points and their troubleshooting, and will also help the quality managementto get decision support in time. But integration and reuse of this knowledge is difficultbecause there are number of challenges e.g., unavailability of unified criteria of FMEAknowledge, lack of semantic organization, natural language text based description ofknowledge, most of the times FMEA is started from scratch instead of using existingknowledge that makes it incomplete for larger systems, and above all its successdepends on the knowledge which is stored in the brains of perfectionists in the formof experience which may or may not be available anytime anywhere. In this article weare proposing an Information and Communication Technology (ICT) based solutionto preserve, reuse, and share the valuable knowledge produced during FMEA. Inproposed system existing knowledge available in repositories and experts head will begathered and stored in a knowledge base using an ontology, and at the time of need thisknowledge base will be inferred to make decisions in order to mitigate the probablerisks. Ontology based approaches are best suited for the knowledge managementsystems, in which human experts are required to model and analyze their expertisein order to feed them in a conceptual knowledge base for its preservation and reuse.

Author Biography

Zobia Rehman, 1. Faculty of Engineering and Management Lucian Blaga University of Sibiu, Romania 2. Department of Computer Science Comsats Institute of Information Technology, Pakistan
Department of Mathematics and Computer Science

References

[1] Carbone, T. A.; Tippett, D.; (2004); Project Risk Management Using the Project Risk FMEA, Engineering Management Journal, 16, 28-35.

[2] Chang, K.H.; Ching, C.H.; (2010); A risk assessment methodology using intuitionistic, International Journal of Systems Science, 1457–1471.

[3] Davenport , T. ; Prusak, L.; (1998); Working knowledge, Boston, MA : Harvard Business School Press.

[4] Dittmann, L. et al (2004); Performing FMEA using ontologies, 18th International workshop on qualitative reasoning, 209–216.

[5] Ebrahimipour, V. et al (2010); An ontology approach to support FMEA studies, Elsevier Expert Systems with Applications, 671-677.

[6] Fernandez, B.I.; Saberwal, R.; (2010); Knowledge Management Systems and Processes, M.E. Sharpe.

[7] Koji, Y. et al (2005); Ontology-based transformation from an extended functional model to FMEA, International conference on engineering design, Melbourne.

[8] Larson, E. W.; Gray, C. F.; (2011); Project Management: The Managerial Process (5th Edition ed.), McGraw Hill.

[9] Laaroussi, A. et al (2007); Ontology-aided FMEA for construction products, J. IEEE Press, 189-194.

[10] LEE, C.F.; (2001); Using FMEA models and ontologies to build diagnostic models, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 281-293.

[11] Mansouri, D.; Hamdi-Cherif, A.; (2011); Ontology-oriented case-based reasoning (CBR) approach for trainings adaptive delivery, 15th WSEAS Int. Conf. on Computers (CSCC2011), 328-333.

[12] Mikos, W.L. et al (2011); A system for distributed sharing and reuse of design and manufacturing, Elsevier Journal of Manufacturing Systems, 133-143.

[13] Molhanec, M. et al (2010); The Ontology based FMEA of Lead Free Soldering Process, International Spring Seminar on Electronics Technology, ISSE.

[14] Natalya, F. N.; Deborah, L. M.; (2001); Ontology Development 101: A Guide to Creating Your First Ontology, http://protege.stanford.edu/publications/ontology_development/ontology101.html.

[15] PMI; (2000); Project Management Body of Knowledge Guide PMBOK. Pennsaylvania: project management body of knowledge guide PMBOK.

[16] Pouchard, Line; Ivezic, Nenad; Schlenoff, Craig (March 2000); Ontology Engineering for Distributed Collaboration in Manufacturing, Proceedings of the AIS2000 conference.

[17] Sharman, R. et al (2007); Ontologies A hand book of principles, concepts, and applications in information systems, Springer.

[18] Stamatis, D.H.; (2003); Failure mode and effect analysis: FMEA from theory to execution, USA: ASQ Quality Press.

[19] Wang, Y.M. et al (2009); Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean, Elsevier Expert Systems with Applications, 1195-1207.

[20] Xiuxu, Z.; Yuming, Z.; (2012); Application Research of Ontology-enabled Process FMEA Knowledge Management Method, Int. J. Intelligent Systems and Applications, 34-40.

[21] Zuniga, G.L.; (2001); Ontology: Its transformation from philosophy to information system, Proceedings of international conference on formal ontology, 187-197.
http://dx.doi.org/10.1145/505168.505187
Published
2014-06-15
How to Cite
REHMAN, Zobia; KIFOR, Stefania. A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 9, n. 4, p. 463-470, june 2014. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1167>. Date accessed: 11 aug. 2020. doi: https://doi.org/10.15837/ijccc.2014.4.1167.

Keywords

Knowledge Management (KM), ontology, Failure Mode and Effects Analysis (FMEA)