Machine learning on overlay virtual metrology
AssigneeTaiwan Semiconductor Manufacturing Go. Ltd.
InventorsTzu-Cheng Lin, Y.Y. Peng, Jerry Wang, Kewei Zuo, Chien Rhone Wang
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Abstract
The current disclosure describes techniques for managing vertical alignment or overlay in semiconductor manufacturing using machine learning. Alignments of interconnection features in a fan-out WLP process are evaluated and managed through the disclosed techniques. Big data and neural networks system are used to correlate the overlay error source factors with overlay metrology categories. The overlay error source factors include tool related overlay source factors, wafer or die related overlay source factors and processing context related overlay error source factors.
Claims20
A method, comprising:
- determining a tool position of a wafer processing tool with respect to forming a first feature on a first wafer;
- determining an item position of a first portion of the first wafer corresponding to the first feature;
- determining an overlay metrology with respect to the first feature;
- generating a data set including the tool position, the item position and the overlay metrology;
- and
- generating a function correlating one or more of the tool position or the item position on a first side of the function with the overlay metrology on a second side of the function through machine learning based on the data set.
A system, comprising:
- a wafer processing tool configured to form a feature on a wafer;
- a metrology tool configured to measure an overlay alignment of the feature on the wafer;
- an overlay modeling tool configured to generate an estimated overlay alignment metrology of the feature based on one or more of an alignment parameter of the wafer processing tool or an alignment parameter of the wafer;
- and
- a process control tool configured to adjust one or more of the alignment parameter of the wafer processing tool or the alignment parameter of the wafer based on the estimated overlay alignment metrology.
A computing system, comprising:
- a processor;
- and
- a storage unit have executable instructions stored thereon which, when executed by the processor, configures the processor to implement actions including:
- receiving data on a tool position of a wafer processing tool with respect to forming a first feature on a first wafer;
- receiving data on an item position of a position of the first wafer on a wafer holding tool with respect to the forming the first feature on the first wafer;
- receiving data on a context with respect to the forming the first feature on the first wafer;
- and
- generating a data for adjusting one or more of the tool position or the item position based on applying at least one of the tool position data, the item position data and the context data into a regression model function that correlates at least one of the tool position data, the item position data and the context data with an overlay metrology of the first feature on the first wafer.
Dependencies are inferred from the claim text.