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Ontology-based module selection in the design of reconfigurable machine tools

Author

Listed:
  • Zhenjun Ming

    (Beijing Institute of Technology)

  • Cong Zeng

    (Beijing Institute of Technology)

  • Guoxin Wang

    (Beijing Institute of Technology)

  • Jia Hao

    (Beijing Institute of Technology)

  • Yan Yan

    (Beijing Institute of Technology)

Abstract

Reconfigurable machine tools (RMTs) are important equipment for enterprises to cope with ever-changing markets because of their flexibility. In design of such equipment, selection of appropriate modules is a very critical decision factor to effectively and efficiently satisfy manufacturing requirements. However, the selection of appropriate modules is a challenging task because it is a multi-domain mapping process relying heavily on experts’ domain knowledge, which is usually unstructured and implicit. To effectively support RMT designers, an ontology-based RMT module selection method is proposed. First, a knowledge base is built by development of an ontology to formally represent the taxonomy, properties, and causal relationships of/among three domain core concepts, namely, machining feature, machining operation, and RMT module involved in RMT design. Second, a four-step sequential procedure is established to facilitate the utilization of encoded knowledge from a knowledge base to aid in the selection of appropriate RMT modules. The procedure takes a given part family as the input, automatically infers the required machining operations as well as the RMT modules through rule-based reasoning, and eventually forms a set of RMT configurations that are capable of machining the part family as the output. Finally, the efficacy of the ontology-based RMT module selection method is demonstrated using a plate family manufacturing example. Results show that the approach is effective to support designers by appropriately and rapidly selecting modules and generating configurations in RMT design.

Suggested Citation

  • Zhenjun Ming & Cong Zeng & Guoxin Wang & Jia Hao & Yan Yan, 2020. "Ontology-based module selection in the design of reconfigurable machine tools," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 301-317, February.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:2:d:10.1007_s10845-018-1446-3
    DOI: 10.1007/s10845-018-1446-3
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    References listed on IDEAS

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    1. Claire Palmer & Esmond N. Urwin & Ali Niknejad & Dobrila Petrovic & Keith Popplewell & Robert I. M. Young, 2018. "An ontology supported risk assessment approach for the intelligent configuration of supply networks," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1005-1030, June.
    2. Sihan Huang & Guoxin Wang & Xiwen Shang & Yan Yan, 2018. "Reconfiguration point decision method based on dynamic complexity for reconfigurable manufacturing system (RMS)," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1031-1043, June.
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    Cited by:

    1. Yuming Guo, 2023. "Towards the efficient generation of variant design in product development networks: network nodes importance based product configuration evaluation approach," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 615-631, February.

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