Automated Submicrometer Defect Detection During VLSI Circuit Production

Abstract

Statistical monitoring and control procedures are essential components of VLSI manufacturing operations. Inspection of defects, measurement of critical dimensions and measurement of registration overlay are the traditional methods of monitoring and controlling a photolithography process. This paper will focus on one function of a fully automated inspection system being developed by OSI; the automated detection of defects on multilayer patterned wafers with textured thin films. A system architecture is described consisting of integrated mechanical, electrical, optical and software components that have been tailored to the inspection of semiconductor device micropatterns. A brief review of vision algorithms is presented along with a comparison of the template matching approach and a new method introduced by OSI. The discussion includes the effects of normal process variations and texture of device patterns on defect detection and false defect rates. Finally, the paper will describe the methods in which the data is analyzed and presented to production personnel to establish a rapid means of monitoring and controlling the photolithography process.