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Crack detection in silicon wafers using shearography.


Crack detection in silicon wafers using shearography.

Motamedi, Ramak (2008) Crack detection in silicon wafers using shearography. Masters thesis, Concordia University.

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Defects in silicon wafers affect their mechanical stability considerably during their processing and handling. In the new generation of thin silicon wafers, in addition to subsurface defects, cracks are also one of the most important defects that need to be evaluated. A comprehensive review of literature suggests the use of different techniques for non destructive evaluation (NDE) of silicon wafers. Among the few NDE techniques that can be used for both sub-surface and crack detection, Shearography has the advantage of being a whole field technique that can be utilized as a non-contact method for online inspection. Although, recently shearography has been used for sub-surface defect detection in silicon wafers, the capability of this technique to identify and detect cracks has not been investigated yet. In this work, a shearography system has been developed for nondestructive evaluation of silicon wafers. The optical set-up was arranged and several experiments were carried out to optimize its performance. Batch of perfect wafers, wafers with sub-surface defects and cracked wafers of 500om thickness were qualitatively evaluated using the developed system. Two different loading mechanisms were used to stress the silicon wafer and the advantage of uniform thermal loading over concentrated force loading for crack and sub-surface defect detection has been discussed. In addition to crack detection, the unique potential of the developed system for detection of crack propagation has been discussed.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Motamedi, Ramak
Pagination:xi, 86, [2] leaves : ill. (part col.); 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Thesis Supervisor(s):Sivakumar, Narayanswamy and Hoa, Suong Van
Identification Number:LE 3 C66M43M 2008 M67
ID Code:976221
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:21
Last Modified:13 Jul 2020 20:09
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