Athinia™ provides a secure data analytics platform for collaborating on relevant information from material suppliers and device makers.
Leading-edge semiconductor manufacturing processes are so sensitive that traditional quality control and supply management practices are no longer sufficient to maintain high-yielding integration flows. The rapidly increasing number of process variables requires smart and scalable data and analytical capabilities. To remain competitive, companies need to focus time and resources on the parameters that matter most.
Parameters not captured in CofA account for >60% of variability in manufacturing *
* Based on exemplary use case
Traditional statistical analysis
Every parameter is analyzed separately; some correlations and interactions between parameters are potentially unaccounted for.
Multivariate analysis with Athinia
Data sharing allows all parameters to be correlated in one multivariate analysis; relevant parameters are identified that would have been ignored in traditional analysis.
Gather relevant material, in-process and manufacturing data from within and across companies into a single platform so it can be easily analyzed.
Run multivariate analysis to identify key parameters and opportunities to improve performance.
Take action based on the insights identified and put resources where it really matters to drive performance.
Allow for integrated analysis and control of data by device makers and material suppliers
Provide holistic view and predictions of in-fab performance
Break silos and increase efficiency to solve the most pressing semiconductor manufacturing challenges
Share and analyze the data that matters with your suppliers to help improve yield, efficiency and performance
Focus on the parameters that matter most to material performance and put your effort where it really counts
CASE STUDY
Oftentimes one specific criteria doesn’t meet fab specification limits, and raw material pre-conditioning is a month-long process that can delay customer needs.
CASE STUDY
Batch quality analysis often requires a lengthy data gathering processes involving many different systems. The root cause investigation is typically an intensive, manual processes which can take many days to complete.