Paper Title:
Classification of Defects on Semiconductor Wafers Using Priority Rules
  Abstract

This paper presents a template-based vision system to detect and classify the nonuniformaties that appear on the semiconductor wafer surfaces. Design goals include detection of flaws and correlation of defect features based on semiconductor industry expert’s knowledge. The die pattern is generated and kept as the reference beforehand from the experts in the semiconductor industry. The system is capable of identifying the defects on the wafers after die sawing. Each unique defect structure is defined as an object. Objects are grouped into user-defined categories such as chipping, metallization peel off, silicon dust contamination, etc., after die sawing and micro-crack, scratch, ink dot being washed off, bridging, etc., from the wafer. This paper also describes the vision system in terms of its hardware modules, as well as the image processing algorithms utilized to perform the functions.

  Info
Periodical
Defect and Diffusion Forum (Volumes 230-232)
Edited by
David J. Fisher
Pages
135-148
DOI
10.4028/www.scientific.net/DDF.230-232.135
Citation
N.G. Shankar, Z.W. Zhong, N. Ravi, "Classification of Defects on Semiconductor Wafers Using Priority Rules ", Defect and Diffusion Forum, Vols. 230-232, pp. 135-148, 2004
Online since
November 2004
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Ya Jing Li, Jie Xin Pu, Qing Hua Zhang
Abstract:In offset printing system, presensitized plate (PS plate) is one of the key factors that influences the quality of printing products. In this...
2112
Authors: Zhong Liang Pan, Ling Chen, Guang Zhao Zhang
III. Display Technologies
Abstract:The defects of LED wafer may be caused from the manufacturing environments such as contamination. The appearance of the defects can results...
251
Authors: Zheng Wang
Chapter 5: Materials Forming
Abstract:Typical characteristics of web manufacturing process ,when compared with other sheet or flat product manufacturing, are the large value of...
426
Authors: Yi Hong Li, Zhao Yang Lu, Jing Li, Ling Ling Cui
Chapter 2: Advanced Manufacturing Systems and Equipment
Abstract:The big differences of the texture and shapes in the same type and certain similarities among heterogeneous types result in the difficult...
634
Authors: Jing Xie, Chang Hang Xu, Guo Ming Chen
Chapter 5: Measurements, Monitoring and Sensor
Abstract:We propose an infrared thermal image processing framework based on a modified fuzzy c-means clustering algorithm with revised similarity...
1356