Quality

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

Visualizations

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.

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.

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.

Semiconductor Manufacturing Quality Management

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