Overview

Athinia Catalyst provides powerful tools to explore, visualize, and analyze your semiconductor manufacturing data. Designed for engineers and analysts, these tools help you uncover hidden patterns, identify correlations, and extract valuable insights without requiring advanced programming or data science skills.

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Access Athinia Catalyst at catalyst.athinia.io.

Getting Started: Learn how to create your first study and upload datasets

Key Features

Data Exploration

• Statistics: Get a comprehensive view of your dataset's characteristics, including distributions, outliers, and data quality metrics
• Filtering: Refine your dataset by creating precise filter conditions to focus on specific subsets of data

Data Visualization

• Plots: Create insightful visualizations using an intuitive drag-and-drop interface
• Correlations: Discover relationships between variables using correlation matrices and ranked correlation views

Machine Learning & Analysis

• Feature Importance: Identify which variables have the greatest impact on your target metrics
• Choosing the Right Scorer: Select appropriate evaluation metrics for your machine learning models

Data Management

• Data Types: Understand how different types of semiconductor data are classified and processed

Use Cases

• Process Optimization: Identify which parameters most strongly influence your yield or quality metrics
• Root Cause Analysis: Uncover correlations between equipment settings and defect patterns
• Quality Control: Build models to predict potential quality issues before they occur
• Process Monitoring: Track critical parameters and identify trends or anomalies