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A rapid virtual assembly approach for 3D models of production line equipment based on the smart recognition of assembly features

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Abstract

Because of the large quantity of three-dimensional (3D) models and the manual operation process used for their virtual assembly, production line assembly design is time consuming and cannot readily meet the requirements of normalization. To address these problems, we propose a rapid virtual assembly approach based on the smart recognition of assembly features and present a system based on this concept. A 3D-two-dimensional (2D)-3D assembly feature recognition mode is proposed. The 3D models are first standardized using a standardization algorithm. The standardized 3D models are subsequently divided into six half parts, and each half part is projected into the coordinate plane to obtain its 2D projection drawing. The contours of the 2D projection drawings are obtained via a contour-recognition algorithm, and segments in contours are classified into different groups according to collinearity. A lightweight 3D model of the original 3D model is created through a series of Boolean operations. Assembly features can be obtained by matching the lightweight 3D model with the original 3D model. The recognized assembly features are used in the rapid assembly system to perform the assembly, and the constraints among these features are automatically added when two models are in proximity. Three comparison tests are conducted, and the results show that the system simplifies the assembly process, greatly increases the assembly design efficiency of the production line, and simultaneously reduces the workload and operational complexity.

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Acknowledgements

This research was financially supported by the Natural Science Foundation of Hubei Province, China (No. 2015CFA115); the National Key Research Plan, China (No. 2016YFB1101701); and Science and Technology Support Program of Hubei Province, China (No. 2015BAA058).

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Authors and Affiliations

  1. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Buyun Sheng, Xiyan Yin, Chenglei Zhang, Feiyu Zhao, Zhenqiang Fang & Zheng Xiao

  2. Dongfeng Design Institute Co., Ltd, Wuhan, 430056, China

    Zhenqiang Fang

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  1. Buyun Sheng
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  2. Xiyan Yin
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  3. Chenglei Zhang
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  4. Feiyu Zhao
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  5. Zhenqiang Fang
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  6. Zheng Xiao
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Correspondence to Xiyan Yin.

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Sheng, B., Yin, X., Zhang, C. et al. A rapid virtual assembly approach for 3D models of production line equipment based on the smart recognition of assembly features. J Ambient Intell Human Comput 10, 1257–1270 (2019). https://doi.org/10.1007/s12652-018-0753-z

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  • DOI: https://doi.org/10.1007/s12652-018-0753-z

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