Integrated circuit probe card troubleshooting based on rough set theory for advanced quality control and an empirical study

Chen-Fu Chien () and Hsin-Jung Wu
Additional contact information
Chen-Fu Chien: National Tsing Hua University
Hsin-Jung Wu: National Tsing Hua University

Journal of Intelligent Manufacturing, 2024, vol. 35, issue 1, No 16, 275-287

Abstract: Abstract Wafer probe test plays a crucial role to distinguish the good dies from the remaining defected dies on the wafers via the probe card as the testing signal interface between the tester and the integrated circuits on the fabricated wafers. Unexpected probe card failures that happen during the testing process will affect testing quality, reduce overall equipment efficiency and productivity. In practice, the engineers rely on domain knowledge and the process of trial and error for fault diagnosis and troubleshooting. However, as the IC device features are continuously shrinking with an increasing number and density of the bond pads of the circuits on the wafer, fault diagnosis and troubleshooting for probe card have become complicated and time-consuming. To fill the gap, this study aims to develop a data-driven framework that integrates rough set theory and domain knowledge to derive effective decision rules to enhance the decision quality and efficiency for advanced quality control and smart manufacturing. An empirical study was conducted in a leading semiconductor testing company in Taiwan for validation. The proposed framework can shorten fault diagnosis procedure and enhance productivity, while enhancing probing test integrity to reduce both the producer risk and customer risk. The developed solution is implemented in real setting.

Keywords: Rough set theory; Probe card; Industry 3.5; Advanced quality control (AQC); Semiconductor manufacturing (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-022-02042-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:35:y:2024:i:1:d:10.1007_s10845-022-02042-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-022-02042-8

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().