Machine vision as input to a CMP process control algorithm
During chemical mechanical polishing of a substrate, a signal value that depends on a thickness of a layer in a measurement spot on a substrate undergoing polishing is determined by a first in-situ monitoring system. An image of at least the measurement spot of the substrate is generated by a second in-situ imaging system. Machine vision processing, e.g., a convolutional neural network, is used to determine a characterizing value for the measurement spot based on the image. Then a measurement value is calculated based on both the characterizing value and the signal value.
1. A polishing system, comprising:
a support to hold a polishing pad;
a carrier head to hold a surface of a substrate in contact with the polishing pad;
a motor to generate relative motion between the support and the carrier head;
an in-situ monitoring system to generate a signal comprising a sequence of raw signal values that depends on a thickness of a layer in a measurement spot on the substrate;
an in-situ imaging system to generate an image of at least the measurement spot of the substrate at substantially the same time as the in-situ monitoring system generates the signal for the measurement spot on the substrate; and
a controller configured to
receive the image from the in-situ imaging system,
receive the signal from the in-situ monitoring system,
determine a characterizing value relating to an orientation of the substrate in a portion of the image corresponding to the measurement spot by using machine vision processing of the image to generate the characterizing value,
perform a conversion of the sequence of raw signal values of the signal from the in-situ monitoring system into a sequence of thickness values for the measurement spot by providing the sequence of raw signal values and the characterizing value as input to a conversion algorithm wherein the characterizing value influences the conversion of the sequence of raw signal values to the sequence of thickness values, and wherein each thickness value of the sequence of thickness values represents a thickness of the layer in the measurement spot, and
at least one of halt polishing of the substrate or adjust a polishing parameter based on the thickness value.
2. The system of claim 1 , wherein the machine vision processing comprises an artificial neural network.
3. The system of claim 2 , wherein the machine vision processing comprises a convolutional neural network.
4. The system of claim 2 , wherein the controller is configured to train the artificial neural network by backpropagation using training data including images and known characterizing values for the images.
5. The system of claim 1 , wherein the in-situ monitoring system comprises an eddy current monitoring system to generate a signal value for the measurement spot.
6. The system of claim 1 , wherein the controller is configured to determine a portion of the image that corresponds to the measurement spot.
7. The system of claim 6 , wherein the controller is configured to synchronize image data from the in-situ imaging system with signal values from the in-situ monitoring system.