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Fakulteta za strojništvo, Ljubljana (FSLJ)
  • Towards self-learning autonomous work systems [Elektronski vir]
    Žapčević, Seid ; Butala, Peter, 1953-
    In order to survive in conditions of the highly competitive global economy, manufacturing systems must be able to adapt to new circumstances. The high level of communication and cooperation of ... autonomous manufacturing units within manufacturing networks partially ensures adaptation. However, the autonomous units do not have the ability to learn. Out of ability to learn, autonomous work systems can not adequately adapt and evolve. Therefore, discovery of new knowledge and its integration as a component in manufacturing equipment and management system are key issues of manufacturing research. Learning is a process based on knowledge discovery and growth. Therefore, the aim of this research is to elicit knowledge from huge amount of manufacturing data collected during manufacturing operations and related to products, processes, resources and quality. The gained new knowledge is to be used for: (1) optimization and/or manufacturing system adaptation, (2) products improvement and (3) services improvement. The following issues are discussed: (1) data to be gathered during ongoing operations of autonomous work system, (2) methods and techniques for data gathering, (3) methods for data mining and knowledge discovery that is transmission of data into knowledge at the autonomous work systems level.
    Vir: RIM 2009 [Elektronski vir] : proceedings = zbornik radova (6 str.)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2009
    Jezik - angleški
    COBISS.SI-ID - 11111195

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