article

Knowledge formalization in experience feedback processes: An ontology-based approach

Authors:

B. Kamsu Foguem,

L. GenesteAuthors Info & Claims

Computers in Industry, Volume 59, Issue 7

Pages 694 - 710

https://doi.org/10.1016/j.compind.2007.12.014

Published: 01 September 2008 Publication History

Abstract

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving the missions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable.

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Knowledge formalization in experience feedback processes: An ontology-based approach

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cover image Computers in Industry

Computers in Industry Volume 59, Issue 7

September, 2008

119 pages

ISSN:0166-3615

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Copyright © © 2008.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 September 2008

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https://dl.acm.org/doi/10.1007/s10845-021-01889-7
Mohsen WAref MElBahnasy K(2020)Scaled Scrum Framework for Cooperative Domain Ontology EvolutionProceedings of the 6th International Conference on Frontiers of Educational Technologies10.1145/3404709.3404770(135-143)Online publication date: 5-Jun-2020
https://dl.acm.org/doi/10.1145/3404709.3404770
Barzegar MSadeghi-Niaraki AShakeri MChoi S(2019)An Improved Route-Finding Algorithm Using Ubiquitous Ontology-Based Experiences ModelingComplexity10.1155/2019/95843972019Online publication date: 11-Nov-2019
https://dl.acm.org/doi/10.1155/2019/9584397
Li XJiang ZSong BLiu L(2017)Long-term knowledge evolution modeling for empirical engineering knowledgeAdvanced Engineering Informatics10.1016/j.aei.2017.08.00134:C(17-35)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1016/j.aei.2017.08.001
Song BJiang ZLiu L(2016)Automated experiential engineering knowledge acquisition through Q&A contextualization and transformationAdvanced Engineering Informatics10.1016/j.aei.2016.06.00230:3(467-480)Online publication date: 1-Aug-2016
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Gil Herrera RMartin-Bautista M(2015)A novel process-based KMS success framework empowered by ontology learning technologyEngineering Applications of Artificial Intelligence10.1016/j.engappai.2015.06.02545:C(295-312)Online publication date: 1-Oct-2015
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Kamsu-Foguem BAbanda F(2015)Experience modeling with graphs encoded knowledge for construction industryComputers in Industry10.1016/j.compind.2015.02.00470:C(79-88)Online publication date: 1-Jun-2015
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Kamsu-Foguem BTchuenté-Foguem GFoguem C(2014)Using conceptual graphs for clinical guidelines representation and knowledge visualizationInformation Systems Frontiers10.1007/s10796-012-9360-216:4(571-589)Online publication date: 1-Sep-2014
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