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Machining Feature Recognition Using Descriptors with Range Constraints for Mechanical 3D Models

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Abstract

In machining feature recognition, geometric elements generated in a three-dimensional computer-aided design model are identified. This technique is used in manufacturability evaluation, process planning, and tool path generation. Here, we propose a method of recognizing 16 types of machining features using descriptors, often used in shape-based part retrieval studies. The base face is selected for each feature type, and descriptors express the base face’s minimum, maximum, and equal conditions. Furthermore, the similarity in the three conditions between the descriptors extracted from the target face and those from the base face is calculated. If the similarity is greater than or equal to the threshold, the target face is determined as the base face of the feature. Machining feature recognition tests were conducted for two test cases using the proposed method, and all machining features included in the test cases were successfully recognized. Moreover, we have compared the proposed method with the latest artificial neural network for test cases 3 and 4. As a result, the proposed method demonstrated a significantly higher recognition performance, with F1 scores of 0.94 and 1.0 for test cases 3 and 4, respectively, compared to the latest artificial neural networks (each with F1 scores of 0.86 and 0.49).

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Acknowledgements

This research was supported by the Basic Science Research Program [No. NRF-2022R1A2C2005879] through the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT), by the Carbon Reduction Model Linked Digital Engineering Design Technology Development Program [No. RS-2022-00143813] funded by the Korean government (MOTIE), and by Institute of Information & communications Technology Planning & evaluation (IITP) grant funded by the Korea government (MSIT) [No.2022-0-00969].

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Authors and Affiliations

  1. School of Mechanical Engineering, Korea University, Seoul, 02841, Republic of Korea

    Seungeun Lim, Changmo Yeo & Duhwan Mun

  2. School of Computer Science, Wuhan University, Wuhan, 430072, China

    Fazhi He

  3. Department of Industrial and Management Engineering, Gangneung-Wonju National University, Gangwon-do, 26403, Republic of Korea

    Jinwon Lee

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Contributions

SL: Methodology, Data Curation, Software, Writing - Original Draft. CY: Data Curation, Software, Writing - Original Draft. FH: Resources, Writing – Review & Editing. JL: Methodology, Validation, Investigation, Writing - Review & Editing DM: Supervision, Conceptualization, Methodology, Writing - Review & Editing, Funding.

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Correspondence to Jinwon Lee or Duhwan Mun.

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Lim, S., Yeo, C., He, F. et al. Machining Feature Recognition Using Descriptors with Range Constraints for Mechanical 3D Models. Int. J. Precis. Eng. Manuf. 24, 1865–1888 (2023). https://doi.org/10.1007/s12541-023-00836-1

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