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A knowledge based intelligent process planning method for controller of computer numerical control machine tools

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Abstract

The development of computer, internet and information technology puts forward higher demands for Computer Numerical Control (CNC) machine tools to improve the intelligence in many aspects. Among these aspects, intelligent process planning plays an important role in current changeable market and customized product promotion by shortening production cycle and providing more stable process planning ability. To realize intelligent process planning, a CNC controller with cloud knowledge base support is proposed with ability of making process planning autonomously based on workpiece design. Previous work of knowledge model and cloud knowledge base framework design is introduced, and then this paper focuses on the complete process planning method within the intelligent CNC controller. Both interactivity between knowledge base and CNC controller, and query/infer mechanism in knowledge base are illustrated in detail. A case study of two shafts process planning is shown to demonstrate the feasibility of the intelligent process planning method.

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Acknowledgements

The work is supported by National Natural Science Foundation of China (Grant No. 51405270).

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Authors and Affiliations

  1. School of Mechanical Engineering, Shandong University, Jinan, China

    Yingxin Ye, Tianliang Hu, Yan Yang, Wendan Zhu & Chengrui Zhang

  2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Shandong University), Ministry of Education, Jinan, China

    Yingxin Ye, Tianliang Hu, Yan Yang, Wendan Zhu & Chengrui Zhang

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  1. Yingxin Ye
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  2. Tianliang Hu
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  3. Yan Yang
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  4. Wendan Zhu
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  5. Chengrui Zhang
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Correspondence to Tianliang Hu.

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Ye, Y., Hu, T., Yang, Y. et al. A knowledge based intelligent process planning method for controller of computer numerical control machine tools. J Intell Manuf 31, 1751–1767 (2020). https://doi.org/10.1007/s10845-018-1401-3

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  • DOI: https://doi.org/10.1007/s10845-018-1401-3

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