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An approach to support SMEs in manufacturing knowledge organization

Author

Listed:
  • Giulia Bruno

    (Politecnico di Torino)

  • Teresa Taurino

    (Politecnico di Torino)

  • Agostino Villa

    (Politecnico di Torino)

Abstract

Different kinds of technological data are available in manufacturing enterprises, concerning the resources available as well as the processes and the components needed for the production of specific products. These data usually are not stored in a centralized knowledge management system, thus one of the main problem of managers, especially in small enterprises, is to efficiently manage their data and reuse the knowledge deriving from previous products when a new product has to be produced. Starting form the analysis of the technological data available in manufacturing enterprises, we defined a formal model as set of matrices; their analysis allows the definition of a data model to structure the technological information. The model is at the basis of the proposed system, called manufacturing knowledge organization (MAKO) to support managers in structuring and reusing the technological knowledge available in their enterprise. A prototype of the MAKO system was implemented by using open-source software and its potentialities are shown in a case study.

Suggested Citation

  • Giulia Bruno & Teresa Taurino & Agostino Villa, 2018. "An approach to support SMEs in manufacturing knowledge organization," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1379-1392, August.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:6:d:10.1007_s10845-015-1186-6
    DOI: 10.1007/s10845-015-1186-6
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    References listed on IDEAS

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    1. Paula Andrea Potes Ruiz & Bernard Kamsu-Foguem & Daniel Noyes, 2013. "Knowledge reuse integrating the collaboration from experts in industrial maintenance management," Post-Print hal-00861829, HAL.
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    Cited by:

    1. Zhenyong Wu & Lina He & Yuan Wang & Mark Goh & Xinguo Ming, 2020. "Knowledge recommendation for product development using integrated rough set-information entropy correction," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1559-1578, August.
    2. Gautam Dutta & Ravinder Kumar & Rahul Sindhwani & Rajesh Kr. Singh, 2021. "Digitalization priorities of quality control processes for SMEs: a conceptual study in perspective of Industry 4.0 adoption," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1679-1698, August.

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