Method for detecting silicon chip edge automatically

Abstract

The invention discloses a method for automatically detecting the edge of a silicon chip. The method comprises: step one, an automatic defect detector scans the silicon chip and stores a scanning result to form a file with a KLARF format; step two, a virtual crystal element is added to the KLARF file stored in the step one; the virtual crystal element integrally covers the edge of the whole siliconchip; step three, a coordinate of a detection point of the edge of the silicon chip is calculated in a coordinate system adopted by the KLARF file; step four, the coordinate of the detection point calculated in the step three is used as virtual defect and is added to the KLARF file edited in the step two; and step five, an electron scanning microscope is used to carry out automatic detection on the virtual defect of the KLARF file edited in the step four. Through functional integration of data analytic software and a detection machine, the method realizes automatic detection on the position of the edge of the silicon chip, saves manpower and material resource, improves efficiency and strengthens data accuracy and analyzability.

Description

technical field [0001] The invention relates to a semiconductor manufacturing process, in particular to a method for detecting defects on the edge of a silicon wafer Background technique [0002] At present, integrated circuit manufacturers detect the edge of patterned silicon wafers (that is, silicon wafers that have undergone certain processes such as etching processes on silicon wafers and have formed certain patterns such as etching patterns on silicon wafers) , is manually operated by a scanning electron microscope. [0003] In a production process, in which step is the defect on the edge of the silicon wafer produced, and how the existing defects on the edge of the silicon wafer evolve in the subsequent process? Perform multiple, repeated defect inspections on the wafer edge. This kind of manual detection requires a lot of manpower and material resources, and the efficiency and accuracy are very poor. It is impossible to accurately locate the detection point, and the...

AI Technical Summary

Problems solved by technology

This kind of manual detection requires a lot of manpower and material resources, and the efficiency and accuracy are very poor. It is impossible to accurately locate the detection point, and the analyzability of the data is also poor.

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