Improving capability of recipe management on CD-SEM using recipe diagnostic tool

Abstract

In the semiconductor manufacturing industry, CD-SEM (Critical Dimension -Scanning Electron Microscope) is used for CD measurements on semiconductor wafers. In the CD-SEM, there is a program called "recipe" which is a series of files containing information on measurement conditions (i.e. where, how and what to measure). The recipe controls all of the parameters such as auto focus, pattern recognition and measurement parameters. Depending on the quality of this recipe, there is the possibility of errors in auto focus, pattern recognition and measurements. There are many ways in which to improve the quality of the recipe for better productivity. One method to obtain a higher quality recipe requires the use of a wafer and CD-SEM. When optimizing the recipe, the quality of improvements to the recipe depend heavily on the skill of the engineer, and wafer and CD-SEM conditions. In the semiconductor manufacturing Fab it is very time consuming to optimize recipe errors, as it requires wafer availability, arranging CD-SEM tool time, and analysis of root course of error.This paper discusses a recipe diagnostic tool to evaluate and analyze the root cause of recipe errors. This tool can provide not only analysis of the error root cause, but can also help the user determine how to improve the recipe quality by pinpointing the problematic recipe parameters. This will allow the user to properly select the parameters that need adjustment in order to obtain the best performance recipe possible. This method can reduce engineering time for recipe control by a factor of 10.

Machine-learning-based error detection modeling and feature scoring for error cause analysis of CD-SEMs

“…To reduce recipe creation time, methods to automatically generate appropriate recipes from computer-aided design data have been reported. 1,2 In semiconductor lines, the recipes for current products are sometimes reused for new products as shown in Figure 1. Such inappropriate reused recipes might fail to detect inspection points and result in measurement errors called recipe errors.…”

“…As a result, we need to distinguish whether an error is caused by the recipe or equipment, and examine more detailed parts in recipe configuration or equipment's components. However, previous methods are limited to visualizing error properties 3,4 and require engineers to analyze manually to identify the root cause. Furthermore, measurement processes are becoming more complicated as micro fabrication has advanced.…”