晶粒表面缺陷自動視覺檢測系統之設計與開發

Design and Development of an Automated Visual Inspection System for Die Surface Defects

張元碩(Yuan-Shuo Chang)

指導教授 ： 彭德保

國立交通大學/管理學院/工業工程與管理系所/碩士(2009年)

https://doi.org/10.6842/NCTU.2009.00562

摘要

半導體製造業對產品品質的要求相當嚴謹，因此在晶粒(Die)封裝前的晶粒缺陷檢測是一個品管很重要的過程，傳統的晶粒表面缺陷檢測通常是目視檢測，此方式需要花費大量的人力使用肉眼判斷，不同檢測人員對缺陷的判斷可能不一致，且容易因視覺疲勞產生錯誤判斷或是判斷標準不一致的情形發生。
　　本論文擬針對晶粒表面需要檢驗的缺陷部分，包括：(1)微粒或污染、(2)面積缺損、(3)變色與(4)護層不良等，利用機器視覺技術，提出了一個自動化的檢測演算法。
　　本論文之研究目的在於發展一套以自動視覺檢測系統為基礎的晶粒表面缺陷檢測系統，能檢測出晶粒表面中具有缺陷的晶粒。以提升檢測效率、減少成本，並達成可進行全檢的三項目標。

關鍵字

機器視覺 ； 影像處理 ； 晶粒檢測 ； 缺陷檢測

並列摘要

Product quality is an important factor in semiconductor manufacturing. Therefore, die defect inspection is an important quality control process before packaging. Conventionally, the inspection of die surface defects by human observation is labor intensive. It results in low efficiency and inaccuracy.
This research is to design and develop an automated visual inspection system for die surface defects by using the machine vision technology. The mainly focused inspection items of dice are particles, contaminations, pad missing, pad damage, discoloration, and passivation.
A prototype of the automated visual inspection system for die surface defect inspection will be implemented for inspection efficiency, cost down, and full-inspection.

並列關鍵字

Machine Vision ； Image Processing ； Die Inspection ； Defects Inspection

參考文獻

[1] E. N. Malamas, E. G. M. Petrakis, M. Zervakis, L. Petit, and J. D. Legat, “A survey on industrial vision systems, applications and tools,” Image and Vision Computing, vol. 21, pp. 171-188, 2003.

[2] S. L. Albin and D. J. Friedman, “The impact of clustered defect distributions in IC fabrication,” Management Science, vol. 35, pp. 1066-1078, 1989.

[3] D. J. Friedman and S. L. Albin, “Clustered defects in IC fabrication: impact on process control charts,” IEEE Transactions on Semiconductor Manufacturing, vol. 4, pp. 36-42, 1991.

[4] F. L. Chen and S. F. Liu, “A neural-network approach to recognize defect spatial pattern in semiconductor fabrication,” IEEE Transactions on Semiconductor Manufacturing, vol. 13, pp. 366-373, 2000.

[7] J. K. W. Tobin, T. P. Karnowski, and F. Lakhani, “Integrated applications of inspection data in the semiconductor manufacturing environment,” in Metrology-based Control for Micro-Manufacturing, San Jose, CA, USA, pp. 31-40, 2001.