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

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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.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments on this paper. The authors acknowledge financial support from the National Ministries (JCKY2014602B007), National Natural Science Foundation of China (NSFC 51805033 and 51505032), China Postdoctoral Science Foundation (3030036721802), and Beijing Natural Science Foundation (BJNSF 3172028).

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Correspondence to Guoxin Wang.

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Cite this article

Ming, Z., Zeng, C., Wang, G. et al. Ontology-based module selection in the design of reconfigurable machine tools. J Intell Manuf 31, 301–317 (2020). https://doi.org/10.1007/s10845-018-1446-3

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Keywords

  • Reconfigurable machine tool
  • Design
  • Module selection
  • Ontology
  • SWRL rule
  • Knowledge base