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A product module mining method for PLM database

  • Geological, Civil, Energy and Traffic Engineering
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Abstract

Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management (PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering (FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.

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Authors and Affiliations

  1. School of Power and Mechanical Engineering, Wuhan University, Wuhan, 430072, China

    Tiao-yu Lei  (雷佻钰), Wei-ping Peng  (彭卫平), Jin Lei  (雷金), Yuan-hua Zhong  (钟院华), Qiu-hua Zhang  (张秋华) & Jun-hao Dou  (窦俊豪)

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  1. Tiao-yu Lei  (雷佻钰)
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  2. Wei-ping Peng  (彭卫平)
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  3. Jin Lei  (雷金)
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  4. Yuan-hua Zhong  (钟院华)
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  5. Qiu-hua Zhang  (张秋华)
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  6. Jun-hao Dou  (窦俊豪)
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Corresponding author

Correspondence to Jin Lei  (雷金).

Additional information

Foundation item: Project(51275362) supported by the National Natural Science Foundation of China; Project(2013M542055) supported by China Postdoctoral Science Foundation Funded

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Lei, Ty., Peng, Wp., Lei, J. et al. A product module mining method for PLM database. J. Cent. South Univ. 23, 1754–1766 (2016). https://doi.org/10.1007/s11771-016-3229-3

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  • DOI: https://doi.org/10.1007/s11771-016-3229-3

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