Data Analytics

Data Analytics

KLA’s data analytics systems centralize and analyze the data produced by inspection, metrology and process systems. Using advanced data analysis, modeling and visualization capabilities, our comprehensive suite of data analytics products support applications such as run-time process control, defect excursion identification, wafer and reticle dispositioning, scanner and process corrections, and defect classification. By providing chip and wafer manufacturers with relevant root cause information, our data management and analysis systems accelerate yield learning rates and reduce production risk.

5D Analyzer®

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5D Analyzer®

Advanced Data Analysis and Patterning Control

5D Analyzer® is a run-time process control solution with supporting analytics and visualization for advanced node process optimization, process monitoring and patterning control. It accepts data from a broad range of sources across the fab, including: overlay, reticle registration, wafer geometry, chamber temperature, films, CD, and profile metrology systems; process tools; and scanners. With applications such as advanced overlay analysis and correlation of reticle and wafer shape data to patterning errors, 5D Analyzer enables a variety of offline and real-time use cases for advanced patterning control.

Applications
Run-time process control, Overlay control, Scanner qualification, Scanner correction, Process correction, Patterning control
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Klarity®

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Klarity®

Automated Defect and Yield Data Analysis

Klarity® Defect automated defect analysis and data management system helps fabs achieve faster yield learning cycles through real-time excursion identification. Klarity® SSA (Spatial Signature Analysis) analysis module for Klarity Defect provides automatic detection and classification of defect signatures that indicate process issues. Klarity® ACE XP advanced yield analysis system helps fabs capture, retain and share yield learning within and across fabs for yield acceleration. Klarity systems utilize an intuitive decision flow analysis, allowing engineers to easily create customized analyses that support applications such as lot dispositioning, review sampling, defect source analysis, SPC setup and management, and excursion notifications. Klarity Defect, Klarity SSA and Klarity ACE XP form a fab-wide yield solution that automatically reduces defect inspection, classification and review data to relevant root-cause and yield-analysis information. Klarity data helps IC, packaging, compound semi and HDD manufacturers take corrective action sooner, resulting in accelerated yield and better time to market.

Applications

Defect data analysis, Wafer disposition, Process and tool excursion identification, Spatial signature analysis, Yield analysis, Yield prediction

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Anchor Die to Database Pattern Monitor

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Anchor Die to Database Pattern Monitor

Automated Defect Detection and Monitoring Solution

The Anchor Die to Database Pattern Monitor provides unique and accurate functionality to extract yield-limiting issues by analyzing SEM images in combination with the chip design. Successfully field-tested and adopted at multiple top tier fabs around the world, Anchor Die to Database Pattern Monitor:

  • Applies a knowledge-based approach for a smart and efficient selection of care areas for wafer monitoring
  • Expands the scope and effectiveness of yield learning without incurring the burden of extra data collection or manual analysis
  • Integrates into the wafer fab workflow and supports product life cycle from development and pilot ramp through high-volume production
  • Accommodates images from all SEM and inline e-beam images

Applications

Process development, Process qualification, Yield ramp, Yield monitoring

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Anchor Pattern Centric Yield Manager

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Anchor Pattern Centric Yield Manager

Automated Design Decomposition and Pattern Risk Scoring

The Anchor Pattern Centric Yield Manager begins by creating the design decomposition database using a set of parametric search rules to extract patterns of interest. Patterns in the Design Decomposition Database are then scored based on all available information sources, including OPC simulation, statistical or geometrical sources (design signatures), and empirical sources such as pattern fidelity information extracted from SEM images. When all patterns are scored (or ranked), Anchor Pattern Centric Yield Manager:

  • Assesses the process marginality or risk of each pattern and generates pattern risk score trends over time
  • Compares a new tape-out against a reference design to identify pattern risk factors
  • Creates optical and e-beam inspection care areas
  • Performs improved defect sampling for SEM review
  • Provides pattern risk feedback to OPC / Lithography teams

Applications

Process development, Process qualification, Yield ramp, Yield monitoring

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Anchor Pattern Centric Machine Learning

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Anchor Pattern Centric Machine Learning

Automated Design Decomposition and Parametric Rules Search

The Anchor Pattern Centric Machine Learning bridges the printed pattern database and the Design Decomposition Database to enable entirely new opportunities for yield learning and process optimization by predicting pattern risk scores that are more reliable than purely statistical or geometrical signatures. Anchor Pattern Centric Machine Learning:

  • Builds a machine learning model from the data contained in the Printed Pattern Database
  • Predicts pattern risk scores on nearly all the patterns contained in the much larger Design Decomposition Database
  • Captures new SEM images that are continuously generated in the fab into the Printed Pattern Database
  • Enables continuous learning to improve its prediction accuracy moving it closer to an expert system

Applications

Process development, Process qualification, Yield ramp, Yield monitoring

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SPOT®

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SPOT®

Automated predictive analytics for fab process and yield management

SPOT® (Sample Plan Optimization Toolkit) is a production machine learning platform used in chip manufacturing fabs. It improves the capture rate of critical defects of interest (DOI) by using a combination of customizable machine learning techniques and statistical algorithms. Inspection and review data is comprehensively analyzed on powerful, scalable computing architecture, using advanced machine learning models to identify and predict real defects of interest and separate them from nuisance defects. An optimized, targeted review sample plan is automatically generated which can discover more DOI and show wafer signatures previously buried in nuisance noise.

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RDC

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RDC

Reticle Data Analysis and Management

The RDC (Reticle Decision Center) comprehensive data analysis and management system supports multiple KLA reticle inspection and metrology platforms for reticle qualification. RDC provides a wide array of applications that drive automated defect disposition decisions, improve cycle time and reduce the reticle-related patterning errors that can affect yield. In addition to providing critical applications, RDC serves as a central data management system utilizing a high reliability, flexible server configuration.

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ProDATA

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ProDATA

Process Window Analysis

ProDATA™ V2.1 process window analysis software provides a systematic, robust approach to understanding and optimizing lithography processes across the fab. This powerful software speeds critical decision making by enabling fast, easy and accurate analysis of experimental data, including critical dimension (CD) analysis, roughness, sidewall angle, top loss and pattern collapse.

Applications
Stepper qualification, Lithography process optimization, Reticle verification and qualification, Lithography tool monitoring data analysis, Photoresist performance analysis
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