Paper
6 May 1993 Automatic defect classification system for semiconductor wafers
Rivi Sherman, Ehud Tirosh, Zeev Smilansky
Author Affiliations +
Proceedings Volume 1907, Machine Vision Applications in Industrial Inspection; (1993) https://doi.org/10.1117/12.144824
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States
Abstract
The problem of automated defect classification has been recognized as one of the biggest challenges to successful integration of automated inspection into wafer manufacturing process. The high degree of customization required for each application adds another dimension to the inherent difficulties. For example, the input to an automatic classifier of printed circuit boards defects will be completely different from the input to a semiconductor defect classifier. Also, the heuristics used for classification will differ greatly. Furthermore, even in similar applications, different manufacturers will have different notions of how defects ought to be classified. In this paper we describe a system which attempts to automate the defect classification process, offering a high degree of adaptivity, customization and automation, with special emphasis on minimizing the need for input from a skilled user. Using Orbot's wafer inspection system, we concentrated on classification of defects on patterned wafers.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rivi Sherman, Ehud Tirosh, and Zeev Smilansky "Automatic defect classification system for semiconductor wafers", Proc. SPIE 1907, Machine Vision Applications in Industrial Inspection, (6 May 1993); https://doi.org/10.1117/12.144824
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CITATIONS
Cited by 11 scholarly publications.
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KEYWORDS
Semiconducting wafers

Inspection

Classification systems

Image classification

Contamination

Scene classification

Machine vision

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