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Selection and sequencing of machining processes for prismatic parts using process ontology model
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  • 作者:Mujin Kang ; Gyungha Kim ; Taemoon Lee…
  • 关键词:Machining processes selection ; Machining processes sequencing ; Process ontology
  • 刊名:International Journal of Precision Engineering and Manufacturing
  • 出版年:2016
  • 出版时间:March 2016
  • 年:2016
  • 卷:17
  • 期:3
  • 页码:387-394
  • 全文大小:569 KB
  • 参考文献:1.Poole, D. L. and Mackworth, A. K., “Artificial Intelligence: Foundations of Computational Agents,” Cambridge University Press, pp. 491–548, 2010.
    2.García, L. E. R., Garcia, A., and Bateman, J., “An Ontology-based Feature Recognition and Design Rule Checker for Engineering,” Proc. of 10th International Semantic Web Conference, pp. 48–58, 2011.
    3.Lemaignan, S., Siadat, A., Dantan, J.-Y., and Semenenko, A., “Mason: A Proposal for an Ontology of Manufacturing Domain,” Proc. of IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications, pp. 195–200, 2006.
    4.Tao, F., Hu, Y., Ding, Y., Sheng, B., Song, C., and Zhou, Z., “Modelling of Manufacturing Resource in Manufacturing Grid based on XML,” Proc. of IEEE International Conference on Industrial Informatics, pp. 1261–1266, 2006.
    5.Feng, S. C. and Song, E. Y., “A Manufacturing Process Information Model for Design and Process Planning Integration,” Journal of Manufacturing Systems, Vol. 22, No. 1, pp. 1–15, 2003.MathSciNet CrossRef
    6.Feng, S. C. and Song, E. Y., “Information Modeling of Conceptual Process Planning Integrated with Conceptual Design,” Proc. of the 5th ASME Design Engineering Technical Conferences, DETC00/ DFM, 2000.
    7.Chungoora, N. and Young, R. I. M., “The Configuration of Design and Manufacture Knowledge Models from a Heavyweight Ontological Foundation,” International Journal of Production Research, Vol. 49, No. 15, pp. 4701–4725, 2011.CrossRef
    8.Chungoora, N. and Young, R. I. M., “Semantic Interoperability Requirements for Manufacturing Knowledge Sharing,” Enterprise Interoperability iii, pp. 411–422, 2008.CrossRef
    9.Muljadi, H., Takeda, H., and Ando, K., “A Feature Library as a Process Planners’ Knowledge Management System,” IJCSNS International Journal of Computer Science and Network Security, Vol. 7, No. 5, pp. 127–135, 2007.
    10.Muljadi, H., Takeda, H., and Ando, K., “Development of a Wiki-Based Feature Library for s Process Planning System,” International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, Vol. 1, No. 9, pp. 468–473, 2007.
    11.Muljadi, H., Ando, K., Takeda, H., and Kanamaru, M., “Considering Designer’s Intention for the Development of Feature Library of a Process Planning System,” Knowledge Sharing in the Integrated Enterprise, pp. 381–388, 2005.CrossRef
    12.Khoshnevis, B., Sormaz, D. N., and Park, J. Y., “An Integrated Process Planning System using Feature Reasoning and Space Search-based Optimization,” IIE transactions, Vol. 31, No. 7, pp. 597–616, 1999.
    13.Patil, L. and Pande, S. S., “An Intelligent Feature-based Process Planning System for Prismatic Parts,” International Journal of Production Research, Vol. 40, No. 17, pp. 4431–4447, 2002.CrossRef MATH
    14.Gao, J. X. and Huang, X. X., “Product and Manufacturing Capability Modelling in an Integrated CAD/Process Planning Environment,” The International Journal of Advanced Manufacturing Technology, Vol. 11, No. 1, pp. 43–51, 1996.MathSciNet CrossRef
    15.ISO 10303–224, “Industrial Automation Systems and Integration -Product Data Representation and Exchange -Part 224: Application Protocol: Mechanical Product Definition for Process Planning using Machining Features,” 2006.
    16.Eum, K., Kang, M., Kim, G., Park, M. W., and Kim, J. K., “Ontology-based Modeling of Process Selection Knowledge for Machining Feature,” Int. J. Precis. Eng. Manuf., Vol. 14, No. 10, pp. 1719–1726, 2013.CrossRef
    17.Kang, M., Kim, G., Eum, K., Park, M. W., and Kim, J. K., “A Classification of Multi-Axis Features based on Manufacturing Process,” Int. J. Precis. Eng. Manuf., Vol. 15, No. 6, pp. 1255–1263, 2014.CrossRef
    18.Kim, J. K., Ahn, W., and Park, M. W., “An Implementation of Webbased Machining Operation Planning,” Proc. of DAAAM International Symposium on Intelligent Manufacturing and Automation, Vol. 100, pp. 1062–1067, 2015.
  • 作者单位:Mujin Kang (1)
    Gyungha Kim (1)
    Taemoon Lee (1)
    Chang Ho Jung (1)
    Kwangho Eum (2)
    Myon Woong Park (3)
    Jae Kwan Kim (3)

    1. School of Mechanical Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, South Korea
    2. C4 Advanced Technology Team, LG Production Engineering Research Institute, 222, LG-ro, Jinwi-myeon, Pyeongtaek-si, Gyeonggi-do, 17709, South Korea
    3. Center for Bionics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil, Seongbuk-gu, Seoul, 02792, South Korea
  • 刊物类别:Engineering
  • 刊物主题:Industrial and Production Engineering
    Materials Science
  • 出版者:Korean Society for Precision Engineering, in co-publication with Springer Verlag GmbH
  • ISSN:2005-4602
文摘
An essential part of process planning is to select the appropriate manufacturing processes and to determine their order from manufacturing knowledge. Ontology technology is considered an effective alternative for knowledge representation. Some studies have suggested a good process knowledge representation model based on heavyweight ontology, but this has inevitably resulted in limited scalability. Other studies have proposed frameworks to reason the appropriate machining processes for a feature, but have not sufficiently taken into account the manufacturing requirements. This paper thus presents an approach to select and sequence the machining processes for features using an ontology-based representation model as well as the corresponding inference rules. The ontology includes concepts including features, machining process, process capability with relevant properties, and relationships between concepts. The reasoning mechanism deduces a set of appropriate machining processes for individual features. Among these is the most appropriate final process determined by matching the accuracy requirements of a specific feature with the capability of the candidate processes. The preceding machining process is then selected so that the precedence relationship constraint between the processes is met until no further precedent processes are required. The proposed approach is neutral in that it is not subject to a specific restriction, such as a particular tool maker, and therefore can provide an interoperable and reusable platform.

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