Paper
15 April 2010 HVM die yield improvement as a function of DRSEM ADC
Sonu Maheshwary, Terry Haas, Steve McGarvey
Author Affiliations +
Abstract
Given the current manufacturing technology roadmap and the competitiveness of the global semiconductor manufacturing environment in conjunction with the semiconductor manufacturing market dynamics, the market place continues to demand a reduced die manufacturing cost. This continuous pressure on lowering die cost in turn drives an aggressive yield learning curve, a key component of which is defect reduction of manufacturing induced anomalies. In order to meet and even exceed line and die yield targets there is a need to revamp defect classification strategies and place a greater emphasize on increasing the accuracy and purity of the Defect Review Scanning Electron Microscope (DRSEM) Automated Defect Classification (ADC) results while placing less emphasis on the ADC results of patterned/un-patterned wafer inspection systems. The increased emphasis on DRSEM ADC results allows for a high degree of automation and consistency in the classification data and eliminates variance induced by the manufacturing staff. This paper examines the use of SEM based Auto Defect Classification in a high volume manufacturing environment as a key driver in the reduction of defect limited yields.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sonu Maheshwary, Terry Haas, and Steve McGarvey "HVM die yield improvement as a function of DRSEM ADC", Proc. SPIE 7638, Metrology, Inspection, and Process Control for Microlithography XXIV, 763822 (15 April 2010); https://doi.org/10.1117/12.846700
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KEYWORDS
Manufacturing

Inspection

Scanning electron microscopy

Image processing

Semiconducting wafers

Image classification

Semiconductor manufacturing

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