Growing variables, tighter requirements:
The imperative for more advanced analytical tools

Semiconductor manufacturing is a complex and intricate process with ever-growing process variables and tighter quality requirements. To remain competitive, companies need stronger data and analytical capabilities to uncover connections between various parameters and improve yield and performance.
In traditional statistical analysis, some correlations and interactions among parameters are missed. With Athinia's multivariate analysis, all relevant parameters are identified so that device makers can focus their resources where it matters most.

Athinia's process & quality analytics tools enable device makers, materials suppliers and equipment makers to:

  • Get greater insight into quality variance earlier in the value chain
  • Minimizes deviations and optimizes costs
  • Reduces time to bring new offerings to market

Athinia bridges the gaps between process engineering and data science

The ecosystem provides a wide array of composable templates for self-service, no-code data analytics

Feature Reduction

  • PCA
  • PLS
  • Linear Correlation
  • TSNE
  • Lasso Regression

Descriptive/ Predictive Models

  • OLS Linear Regression
  • Logistic Regression
  • XGBosst Regressor
  • Random Forest


  • Box Plots
  • Scatter Plots
  • Feature Importance
  • Trend Charts
  • Correlation Matrix

Athinia's recommendation engine suggests model and surfaces data issues

  • Customer datasets are tested against
    hundreds of assumptions, curated and maintained by our data science team
  • Tool clearly identifies limitations in the source data and suggests improvements
  • Suitable algorithms are highlighted and can
    be deployed with a few clicks
  • Assumptions are tested continuously as the underlying data updates

Case Studies

How Mircon scaled its advanced predictive manufacturing with end-to-end data integration and analysis

To address the exponentially growing parameters in semiconductor manufacturing, Micron and EMD Electronics enabled a scalable platform for end-to-end integration and analysis from raw materials to device making.
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Ensure "first-time right" material pre-conditioning with secure data sharing

Whenever a material parameter fails to meet fab specification limits, it can cause delays in meeting customer needs.
Discover how to achieve first-time right material pre-conditioning to save time and resources.
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Accelerate root cause analysis with integrated data access

Root cause investigation is typically an intensive, manual process that can take many days to complete.
Explore how you can quickly identify and correct quality deviation root causes with integrated data access.
Read More