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SmartGallery Technology for ADC Enhances Fab Productivity

by Phil March, Verlyn Fischer, KLA-Tencor Corporation

The benefits of Automatic Defect Classification (ADC) are considerable: speed, reproducibility and reliability that do not fluctuate when the production shift changes.1 When defects are classified consistently, accurately and quickly, defectivity can be effectively monitored by type — a more valuable strategy than monitoring total defect count.2 However, as product life cycles continue to shorten throughout the industry, and as foundries require the ability to implement simple modifications of defectivity control strategies to respond to their rapid changes in product mix, minimizing the time and expertise required to set up the ADC system has gained importance.

Recently, KLA-Tencor introduced a new ADC system, IMPACT XP™, which incorporates an innovative, visually intuitive user interface that provides faster computation and significant improvements to ease of use. Prototype investigations were conducted at two large semiconductor manufacturing sites — one in the U.S. and one in Japan.

At both these sites IMPACT XP was shown to reduce ADC setup time by a factor of three. The reduction in set-up time together with simplification of the set-up process, lowers the barriers to implementation of ADC. Opportunities for improving ADC

New requirements for the ADC system include not only faster set-up of the system, but also a reliable and accurate set-up process that results in production-worthy classifiers. Where do the opportunities for speeding up the ADC set-up time lie?

Thorough training of the ADC system can require upwards of 1000 manually classified images per layer. A scheme for classifying the defects evolves as the defects are imaged, through a combination of automatic algorithms and input from the user. The user selects a set of representative defect images that are used for training the ADC system

and building a knowledge base of recognizable defects.

After training the system the classifiers are verified, then optimized iteratively with reference to the calculated confidence levels for the classes. A team from KLA-Tencor examined each of these steps and focused on the classifier creation area, where 80 percent of the improvement was made. Upgrades to the ADC manager hardware accounted for the remaining 20 percent of the reduction time.3 New tool speeds ADC set-up

IMPACT XP was designed to meet the challenges of faster and easier ADC set-up. A key component of IMPACT XP is SmartGallery™, an innovative technology that allows users to look at images of all defect types from a given layer at the same time before defining the classification scheme (Figure 1). It’s intuitive user interface with drag-and-drop capability allows the user to view and compare multiple defect images simultaneously. This allows quick ADC classifier set-up and facilitates verification and optimization of classifiers through real-time feedback on classifier performance.

SmartGallery combines the ability to view and manipulate a gallery of images with verification tools and real-time feedback on the confidence level of a given class. To simplify optimization of the classifiers, separate galleries are incorporated for the working image set and the training image set, with full sorting capability.

Seeing all the relevant data in one place, simultaneously, strongly enhances the ability of the user to guide the Spring 2000

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set-up time of 69 percent5. At the Japanese site, results were very similar. Set-up time reduction was estimated at 56 percent.

Conclusions

F i g u r e 1. IMPA C T X P ’s Smart G a l l e r y technol ogy allows display of all defect images from a single layer simultaneously and provides an intuitive user interface for ADC class set-up, classifier training and optimization.

The SmartGallery technology of IMPACT XP enables a user to set up a classification strategy and train the ADC system in a shorter period of time than previously attainable. Customer evaluations indicated an improvement in ADC set-up time of up to three times. The benefit is largely attributable to a more intuitive graphical user interface, which improves implementation, speeds set-up and offers real-time feedback to aid in the creation of production-worthy classifiers. This innovation in ADC implemen-

design of intelligent, productionworthy classifiers. The user is able to quickly train the ADC system to identify new defect types and build a knowledge base of recognizable defects by process layer, leading ultimately to tighter monitoring of the process.

Prototype results

Experienced and knowledgeable ADC customers at the two manufacturing sites were asked to breakdown the classifier creation process into constituent tasks and assign a baseline duration to each. The customers then used SmartGallery to build and optimize a set of classifiers. They were next asked to estimate the change in baseline values attributable to their use of SmartGallery. Results from work at the customer site in the U.S. are given in Figure 2, demonstrating a reduction in 14

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F i g u re 2. Experienced ADC users at a large semi cond uctor manufacturin g site in t he U.S. were asked to ba seli ne the time for ea ch of the constit uent tasks of ADC set-up, re p r esented by th e graph on t he left .

After us ing Smart G a l l e r y, they were a sked to es timat e the set -up time imp rovemen t, re p res ented b y th e graph on th e righ t. Set- up time was reduced by 69 perc ent.

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tation is expected to drive a significant increase in ADC utilization throughout the industry including foundries (Figure 3), because it improves the efficiency of process monitoring programs.

References 1 . An early re f e rence is “Automatic Defect Classification,” L. Bre a u x , D. Kolar, Solid State Te c h n o l o g y, Vol. 39 No. 12, pp. 89-96 (1996).

2 . See for example “Tracking the Perf o r man ce of Phot o-li th ograp h ic P rocesses with Excursion Monitori n g , “ E r ic H . B o k e l b e r g a nd Michael E. Pariseau, MICRO, Vo l .

16, No., 1, pp. 47-59 (1998).

F i g u r e 3. Th e improved set -up time pr ovided by IMPACT XP ena bles in crea sed uti liza tion of ADC at foundries and ASIC manufacturing sites — where the ability to quickl y modify defect con trol

s t r a t e g i e s i s es pecially 3 . The hard w a re improvements for SmartGallery include dual Pentium II 450 MHz micro p rocessors, 512 MB RAM, RAID arc h it e c t u re, plus upgrades to the hard drive and backup media.

4 . “ R e a l - Time Classification Streamlines Yield Management P rocess,” Rebecca Howland Pinto, Yield Management Solutions, Autumn, pp. 10 – 14 (1999).

cr itical.

5 . Results from IBM study presented at Yield Management Solutions Seminar during SEMICON/West 1999.

For more information please contact: phil.march@kla-tencor.com or v e r l y n . fis c h e r @ k l a - t e n c o r. c o m

KLA-Tencor Trade Show Calendar February 29-March 1

SPIE Microlithography Conference, Santa Clara, California

March 2-3

CMP-MIC, Santa Clara, California

March 15- 16

SEMICON/China, Shanghai, China

April 4-6

SEMICON/Europa, Munich, Germany

April 13-14

Photomask Japan, Yokohama, Japan

April 27-29

Quality Expo, Rosemont, Illinois

May 1-2

Metrology 2000, San Jose, California

May 4-5

SEMICON/Singapore, Singapore

July 5-7

IITC, Burlingame, California

July 10-14

SEMICON/West, San Jose and San Francisco, California Spring 2000

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