View in EDS

A lightweight high precision real-time system for bonding ball–pad localization in industrial packaging inspection.

Saved in:
Bibliographic Details
Title: A lightweight high precision real-time system for bonding ball–pad localization in industrial packaging inspection.
Authors: Wei, Haoran1 (AUTHOR) 2020241835@jsnu.edu.cn, He, Zhenzhi1 (AUTHOR) hezz82@163.com, Ye, Guo1 (AUTHOR) yeguo5818@126.com, Shu, Xiaotong1 (AUTHOR) xiaotongshu98@gmail.com, Peng, Jingshong1 (AUTHOR) PengJinsong_jsicat@163.com, Chen, Tianchi1 (AUTHOR) ctc900112@163.com, Sheng, Lianchao1 (AUTHOR) shenglianchao@163.com, Lu, Xiangning1 (AUTHOR) lxnam89@163.com
Source: Measurement Science & Technology. 2026, Vol. 37 Issue 27, p1-17. 17p.
Subjects: Wire bonding (Electronic packaging), Real-time computing, Artificial neural networks, Inspection & review, Electronic packaging
Abstract: As a critical interconnection technology in chip packaging, wire bonding imposes stringent requirements on the localization accuracy of bonding balls and pads. Conventional vision-based inspection methods often struggle to satisfy real-time constraints when targets are extremely small, densely distributed, and embedded in cluttered, reflective industrial backgrounds. To meet these demands, a real-time high-precision localization approach is proposed based on an improved real-time detection transformer framework, termed Dynamic-Fast-Aware DETR (DFA-DETR). DFA-DETR integrates several task-oriented architectural components to improve feature representation, efficiency, and robustness under bonding ball–pad detection scenarios. Specifically, inspired by FasterNet and ResNet, the backbone is constructed as a lightweight ResNet-FasterBlock network, which uses partial-channel spatial convolution to reduce redundant computation while preserving feature representation capability for tiny targets. Moreover, a SlimNeck structure is employed for efficient feature fusion and further optimized with DySample to replace fixed upsampling, alleviating spatial misalignment across scales for small bonding ball–pad objects. In addition, a magnitude-aware attention module (magnitude-aware linear attention-adaptive intra-scale feature interaction) based on linear attention is incorporated to enhance region discrimination and suppress strong background interference typical in industrial imaging. Experiments on the bonding ball–pad positioning task achieve 77.92% mAP50–95 and 90.47% mAP75, together with an overall F 1-score of 96.62%. The resulting model runs at 86.81 frames per second with 16.30 m parameters, indicating strong potential for real-time industrial deployment. Ablation studies and qualitative analyses further confirm the effectiveness of each component and their complementary effects. Overall, this work provides an accurate and efficient solution for online visual inspection in packaging wire-bonding processes. [ABSTRACT FROM AUTHOR]
Copyright of Measurement Science & Technology is the property of IOP Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 195188675
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A lightweight high precision real-time system for bonding ball–pad localization in industrial packaging inspection.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wei%2C+Haoran%22">Wei, Haoran</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 2020241835@jsnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22He%2C+Zhenzhi%22">He, Zhenzhi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hezz82@163.com</i><br /><searchLink fieldCode="AR" term="%22Ye%2C+Guo%22">Ye, Guo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yeguo5818@126.com</i><br /><searchLink fieldCode="AR" term="%22Shu%2C+Xiaotong%22">Shu, Xiaotong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xiaotongshu98@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Peng%2C+Jingshong%22">Peng, Jingshong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> PengJinsong_jsicat@163.com</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Tianchi%22">Chen, Tianchi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ctc900112@163.com</i><br /><searchLink fieldCode="AR" term="%22Sheng%2C+Lianchao%22">Sheng, Lianchao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> shenglianchao@163.com</i><br /><searchLink fieldCode="AR" term="%22Lu%2C+Xiangning%22">Lu, Xiangning</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> lxnam89@163.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Measurement+Science+%26+Technology%22">Measurement Science & Technology</searchLink>. 2026, Vol. 37 Issue 27, p1-17. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Wire+bonding+%28Electronic+packaging%29%22">Wire bonding (Electronic packaging)</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Inspection+%26+review%22">Inspection & review</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+packaging%22">Electronic packaging</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: As a critical interconnection technology in chip packaging, wire bonding imposes stringent requirements on the localization accuracy of bonding balls and pads. Conventional vision-based inspection methods often struggle to satisfy real-time constraints when targets are extremely small, densely distributed, and embedded in cluttered, reflective industrial backgrounds. To meet these demands, a real-time high-precision localization approach is proposed based on an improved real-time detection transformer framework, termed Dynamic-Fast-Aware DETR (DFA-DETR). DFA-DETR integrates several task-oriented architectural components to improve feature representation, efficiency, and robustness under bonding ball–pad detection scenarios. Specifically, inspired by FasterNet and ResNet, the backbone is constructed as a lightweight ResNet-FasterBlock network, which uses partial-channel spatial convolution to reduce redundant computation while preserving feature representation capability for tiny targets. Moreover, a SlimNeck structure is employed for efficient feature fusion and further optimized with DySample to replace fixed upsampling, alleviating spatial misalignment across scales for small bonding ball–pad objects. In addition, a magnitude-aware attention module (magnitude-aware linear attention-adaptive intra-scale feature interaction) based on linear attention is incorporated to enhance region discrimination and suppress strong background interference typical in industrial imaging. Experiments on the bonding ball–pad positioning task achieve 77.92% mAP50–95 and 90.47% mAP75, together with an overall F 1-score of 96.62%. The resulting model runs at 86.81 frames per second with 16.30 m parameters, indicating strong potential for real-time industrial deployment. Ablation studies and qualitative analyses further confirm the effectiveness of each component and their complementary effects. Overall, this work provides an accurate and efficient solution for online visual inspection in packaging wire-bonding processes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Measurement Science & Technology is the property of IOP Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=195188675
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1088/1361-6501/ae7f3f
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 1
    Subjects:
      – SubjectFull: Wire bonding (Electronic packaging)
        Type: general
      – SubjectFull: Real-time computing
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Inspection & review
        Type: general
      – SubjectFull: Electronic packaging
        Type: general
    Titles:
      – TitleFull: A lightweight high precision real-time system for bonding ball–pad localization in industrial packaging inspection.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wei, Haoran
      – PersonEntity:
          Name:
            NameFull: He, Zhenzhi
      – PersonEntity:
          Name:
            NameFull: Ye, Guo
      – PersonEntity:
          Name:
            NameFull: Shu, Xiaotong
      – PersonEntity:
          Name:
            NameFull: Peng, Jingshong
      – PersonEntity:
          Name:
            NameFull: Chen, Tianchi
      – PersonEntity:
          Name:
            NameFull: Sheng, Lianchao
      – PersonEntity:
          Name:
            NameFull: Lu, Xiangning
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 10
              M: 07
              Text: 2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 09570233
          Numbering:
            – Type: volume
              Value: 37
            – Type: issue
              Value: 27
          Titles:
            – TitleFull: Measurement Science & Technology
              Type: main
ResultId 1