Overview of automatic defect classification

Marylyn Hoy Bennett; Kenneth W. Tobin; Shaun S. Gleason

Overview of automatic defect classification

Marylyn Hoy Bennett, Kenneth W. Tobin, Shaun S. Gleason

Research output: Contribution to conference › Paper › peer-review

5 Scopus citations

Abstract

The facets of integrated circuit (IC) processing is now being challenged by the ever-shrinking circuitry. As device sizes shrink, so does the size of particles or defects causing chip failure. Early particle detection and quick analysis are crucial to successful device fabrication. Since manual inspection is bound to some limitations, a more promising technique is proposed; automatic defect classification (ADC). The key to the implementation of ADC is the development of image analysis algorithms that can be integrated or retrofit to existing defect detection/review tools. The purpose of this article is to provide an overview of ADC methods and expand on current design concepts for use in wafer fabrication.

Original language	English
Pages	272
Number of pages	1
State	Published - 1994
Externally published	Yes
Event	Proceedings of the IEEE/SEMI 1994 Advanced Semiconductor Manufacturing Conference and Workshop - Cambridge, MA, USA Duration: Nov 14 1994 → Nov 16 1994

Conference

Conference	Proceedings of the IEEE/SEMI 1994 Advanced Semiconductor Manufacturing Conference and Workshop
City	Cambridge, MA, USA
Period	11/14/94 → 11/16/94

Cite this

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title = "Overview of automatic defect classification",

abstract = "The facets of integrated circuit (IC) processing is now being challenged by the ever-shrinking circuitry. As device sizes shrink, so does the size of particles or defects causing chip failure. Early particle detection and quick analysis are crucial to successful device fabrication. Since manual inspection is bound to some limitations, a more promising technique is proposed; automatic defect classification (ADC). The key to the implementation of ADC is the development of image analysis algorithms that can be integrated or retrofit to existing defect detection/review tools. The purpose of this article is to provide an overview of ADC methods and expand on current design concepts for use in wafer fabrication.",

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year = "1994",

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note = "Proceedings of the IEEE/SEMI 1994 Advanced Semiconductor Manufacturing Conference and Workshop ; Conference date: 14-11-1994 Through 16-11-1994",

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AU - Tobin, Kenneth W.

AU - Gleason, Shaun S.

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AB - The facets of integrated circuit (IC) processing is now being challenged by the ever-shrinking circuitry. As device sizes shrink, so does the size of particles or defects causing chip failure. Early particle detection and quick analysis are crucial to successful device fabrication. Since manual inspection is bound to some limitations, a more promising technique is proposed; automatic defect classification (ADC). The key to the implementation of ADC is the development of image analysis algorithms that can be integrated or retrofit to existing defect detection/review tools. The purpose of this article is to provide an overview of ADC methods and expand on current design concepts for use in wafer fabrication.

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M3 - Paper

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T2 - Proceedings of the IEEE/SEMI 1994 Advanced Semiconductor Manufacturing Conference and Workshop

Y2 - 14 November 1994 through 16 November 1994

ER -

Overview of automatic defect classification

Abstract

Conference

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