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Intelligent diagnosis of the solder bumps defects using fuzzy C-means algorithm with the weighted coefficients

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Abstract

Solder bump technology has been widely used in electronic packaging. With the development of solder bumps towards higher density and finer pitch, it is more difficult to inspect the defects of solder bumps as they are hidden in the package. A nondestructive method using the transient active thermography has been proposed to inspect the defects of a solder bump, and we aim at developing an intelligent diagnosis system to eliminate the influence of emissivity unevenness and non-uniform heating on defects recognition in active infrared testing. An improved fuzzy c-means (FCM) algorithm based on the entropy weights is investigated in this paper. The captured thermograms are preprocessed to enhance the thermal contrast between the defective and good bumps. Hot spots corresponding to 16 solder bumps are segmented from the thermal images. The statistical features are calculated and selected appropriately to characterize the status of solder bumps in FCM clustering. The missing bump is identified in the FCM result, which is also validated by the principle component analysis. The intelligent diagnosis system using FCM algorithm with the entropy weights is effective for defects recognition in electronic packages.

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Authors and Affiliations

  1. School of Mechanical & Electrical Engineering, Jiangsu Normal University, Xuzhou, 221116, China

    XiangNing Lu & SuYa Wang

  2. State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    TieLin Shi, Lei Su & GuangLan Liao

  3. School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, 30332, USA

    XiangNing Lu & LiYi Li

Authors
  1. XiangNing Lu
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  2. TieLin Shi
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  3. SuYa Wang
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  4. LiYi Li
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  5. Lei Su
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  6. GuangLan Liao
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Correspondence to GuangLan Liao.

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Lu, X., Shi, T., Wang, S. et al. Intelligent diagnosis of the solder bumps defects using fuzzy C-means algorithm with the weighted coefficients. Sci. China Technol. Sci. 58, 1689–1695 (2015). https://doi.org/10.1007/s11431-015-5896-y

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  • DOI: https://doi.org/10.1007/s11431-015-5896-y

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