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Roslan, Ameer Farhan
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Assessment of detection methods for back-end process defects in equipment and devices in semiconductor manufacturing Roslan, Ameer Farhan; Mat Ibrahim, Masrullizam; Zarifie Hashim, Nik Mohd; Mohd Noh, Mohd Syahrin Amri; Sutikno, Tole
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 2: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i2.pp494-503

Abstract

Defect detection plays a pivotal part in the manufacturing process of semiconductors. Defects can be rooted in the product on its own, as well as the tools used to process and make the product, particularly the equipment and machinery used. Defect detection is crucial in semiconductor manufacturing, where even minor flaws can compromise product performance. Defect detection in the backend process of semiconductor manufacturing, specifically in die attach and die bonding, is critical for ensuring product quality and reliability. Die attach involves securing semiconductor chips onto substrates, while die bonding involves connecting wires to the chip. Detecting defects during these processes is vital to prevent issues such as misalignment, inadequate bonding, or contamination, which can lead to malfunctioning chips or devices. Various techniques such as visual inspection, automated optical inspection (AOI), and X-ray imaging are utilized to identify defects like cracks, voids, or irregularities in bond formation. By employing rigorous defect detection measures, manufacturers can uphold stringent quality standards and produce reliable semiconductor devices for various applications.
Co-Authors Mat Ibrahim, Masrullizam Mohd Noh, Mohd Syahrin Amri Tole Sutikno Zarifie Hashim, Nik Mohd