Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume 31, Issue 2, Pages 301-317Publisher
SPRINGER
DOI: 10.1007/s10845-018-1446-3
Keywords
Reconfigurable machine tool; Design; Module selection; Ontology; SWRL rule; Knowledge base
Funding
- National Natural Science Foundation of China [NSFC 51805033, 51505032]
- China Postdoctoral Science Foundation [3030036721802]
- Beijing Natural Science Foundation [BJNSF 3172028]
- [JCKY2014602B007]
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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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