Application of liquid crystal techniques with image processing

Satoshi Suzuki; Takaaki Numajiri; Koji Saso; Naoki Yoshida; Keiji Fujimoto

doi:10.1117/12.361358

27 August 1999 Application of liquid crystal techniques with image processing

Satoshi Suzuki, Takaaki Numajiri, Koji Saso, Naoki Yoshida, Keiji Fujimoto

Proceedings Volume 3884, In-Line Methods and Monitors for Process and Yield Improvement; (1999) https://doi.org/10.1117/12.361358
Event: Microelectronic Manufacturing '99, 1999, Santa Clara, CA, United States

Abstract

Liquid crystal method is one of the techniques for failure analysis. This technique is well known way to identify a failure point on a silicon integrated circuit. However, the tendency of LSI devices in recent years towards smaller feature size, higher density, lower electric power and larger chip size has created a demand for improvement of this technique towards higher accuracy and increased reliability of failure point localization. In this case, we developed a new technique for applying the liquid crystal method. With this technique, we improved four aspects of the analysis: (1) Automatic adjustment of the temperature towards the transference point of the liquid crystal by image processing. (2) Automatic display of the 'hot spot' by image processing. (3) Automatic oscillation of the applied voltage for enhanced visibility of the current leakage point. (4) Minute control of the temperature from the reverse side of the package using a Peltier element. As a result of this improvement, we could realize improved accuracy for the liquid crystal analysis and reliability of failure point localization. This thesis reports how this technique can be established as a working technique for routine failure analysis, with a practical detection sensitivity of about 1 (mu) W. This method should be called LCIP (Liquid Crystal with Image Processing method).

Citation Download Citation

Satoshi Suzuki, Takaaki Numajiri, Koji Saso, Naoki Yoshida, and Keiji Fujimoto "Application of liquid crystal techniques with image processing", Proc. SPIE 3884, In-Line Methods and Monitors for Process and Yield Improvement, (27 August 1999); https://doi.org/10.1117/12.361358

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