CROSS REFERENCE

The present application claims the benefit under 35 U.S.C. § 119 of German Patent Application No. DE 102019215571.5 filed on Oct. 10, 2019, which is expressly incorporated herein by reference in its entirety.

FIELD

The present invention relates to associating features to devices produced on a wafer.

BACKGROUND INFORMATION

Presently, in final testing of devices produced on a wafer, such as chips, each device is measured or tested individually before or after separation of the devices. The measurement/testing aims to obtain one or more device features including an indication about functionality/errors or other data used to determine one or more training or calibration parameters. The calibration parameters are, e.g., used to set calibration bits, which is particularly common for calibrating integrated sensors.

Even after separating the devices, the devices can be identified by a unique wafer ID and can thereby be retracked to a specific position on the wafer. With this method, wafer maps can be reconstructed by plotting the device feature obtained during the measurement/testing process over the reconstructed position in the wafer map.

Due to the various process steps during the fabrication of the devices on the wafers, distinct patterns can be observed on the wafer maps. These patterns originate from process variations, such as etch loss, trench angle mismatch and the like, induced by the processing equipment and on intrinsic variations over the wafer surface.

Also for different wafers produced with same the same devices, i.e., obtained by identical mask layouts and processing steps, the devices will show very similar patterns of device features with respect to their wafer maps.

SUMMARY

In accordance with an example embodiment of the present invention, a method for determining one or more device features for devices produced on a wafer based on sample measurements, and a device are provided.

Further embodiments are described herein.

According to a first aspect of the present invention, a method for determining a device feature of a device produced on a wafer is provided, comprising the steps of:Providing a wafer feature model associating a wafer position indicating a position of a produced device on a wafer to a device feature, wherein the wafer feature model is configured to be trained by one or more wafer feature maps and particularly configured as a Gaussian process model;Providing a sample device feature of at least one device at a subset of of sample wafer positions; andDetermining the device feature of at least one other device of the (same) wafer depending on the provided wafer feature model.

According to the above example method, a device feature model is provided which is trained to associate wafer positions of devices produced on a wafer to one or more device features. The one or more device features may include an indication about functionality/errors or other data such as one or more training or calibration parameters.

Moreover, the wafer feature model may be non-parametric which can be trained using sample data. Furthermore, the wafer feature model may provide an uncertainty value for a predicted feature.

Furthermore, in addition to the wafer positions, the device feature model may optionally associate one or more further operating parameters to the one or more device features.

By means of the device features, a wafer feature map can be build for the wafer positions. Using such a wafer feature map, sample wafer positions of devices can be determined which shall be used for measurement/testing/probing of the respective device features. The subset of the wafer positions may include one or more sample wafer positions. The results of the testing/measuring the devices at the subset of wafer positions are used for determining the respective device features of the devices at the other wafer positions.

The sample wafer positions may be determined by minimizing the predictive uncertainty in terms of given requirement violations. Thereby, only a few devices can be selected for testing/measuring to obtain the corresponding one or more device features which allows to determine the respective device feature for the other devices produced on the same wafer.

Using by the device feature model, the above example method allows to obtain features for all devices of the same or other wafers produced with identical devices just by determining corresponding one or more device features at sample wafer positions. Therefore, the present invention takes advantage of similar patterns of the distribution of one or more device features, which are a result of the common processing steps and processing parameters used for wafer production, for prediction of device features.

By replacing the expensive determination (including physical measurement and testing) of all device features for all devices of the wafer with a corresponding determination for a preselected subset of devices, measurement/testing costs can be reduced significantly. Depending on the accuracy of the wafer feature model and given specification limits for the determined features, only a small part of the devices need to be tested/measured.

Furthermore, the device feature may include of one: an indication of functionality, an indication of an error, an indication whether the device fulfils a given specification, and a calibration parameter to be written/stored into the specific device.

It may be provided that the wafer feature model additionally associates environmental and/or operating conditions to the device feature.

According to an example embodiment of the present invention, the wafer feature model may be trained by providing a number of processed wafers including identical devices, wherein particularly the processed wafers include one or more corner lot wafers.

It may be provided that the sample device feature of the at least one device is obtained at a selected discrete subset of wafer positions which maximizes the likelihood of all samples on the wafer being inside given specification limits.

According to an example embodiment of the present invention, the selected discrete subset of wafer positions is selected by maximizing the likelihood of all samples on the wafer being inside given specification limits slimaccording to

p⁡(d⁡(f)≤slim)≥pminwhereind⁡(f)=∑i∈X⁢fm⁢o⁢d⁡(i)-fdes
and pminis a lower bound on the minimum probability that the specification limit slimis satisfied per sample, wherein X is the set of all wafer positions, fmodis a modelled feature and fdesis the nominal feature which shall be met for the device at the specific position i.

Furthermore, a limit violation v may be specified as

v=p⁡(minfm⁢o⁢d⁡(i)⁢d⁡(f)≤sa⁢c⁢c)
wherein the subset of wafer positions is selected to minimize the probability of expected limit violations over all devices of the wafer.

It may be provided that the subset of wafer positions is updated by means of an acquisition function
a(χsamp)=˜p(∥χ,,θ,ϕ)[v(ysamp−˜p(|χ,,χsamp,samp,θ,ϕ)[v(y)]]
wherein the selecting of the wafer position s for the optimized subset of wafer positions, the acquisition function is evaluated for all possible combinations of wafer positions, wherein the subset of wafer positions with the lowest expected limit violation is selected.

Furthermore, the device feature model may be provided using a prior for the patterns of the corresponding based on prior technological knowledge of the fabrication steps using the processing equipment.

According to another aspect of the present invention, an example computer-implemented method for production of devices on a wafer is provided, comprising the steps of:Controlling a production of the devices on one or more wafers;Determining of a device feature for the devices by means of the above method,
wherein the production of the devices is controlled depending on the determined device feature.

Moreover, the respective device feature may be written into a memory of the devices, particularly as a respective calibration parameter. Additionally or alternatively, the devices are classified or rejected depending on the respective device feature. Furthermore, it may be provided that the production of the devices is halted depending on the respective device features of the devices.

According to a further aspect of the present invention, an example system for determining a device feature of a device produced on a wafer is provided, wherein the system is configured to perform the steps of:Providing a wafer feature model associating a wafer position indicating a position of a produced device on a wafer to a device feature, wherein the wafer feature model is configured to be trained by one or more wafer feature maps and particularly configured as a Gaussian process model;Providing a sample device feature of at least one device at a sample wafer position;Determining the device feature of at least one other device of the wafer depending on the provided wafer feature model.

According to a further aspect of the present invention, an example system for production of devices on a wafer is provided, wherein the system is configured to perform the steps of:Controlling a production of the devices on one or more wafers;Providing a wafer feature model associating a wafer position indicating a position of a produced device on a wafer to a device feature, wherein the wafer feature model is configured to be trained by one or more wafer feature maps and particularly configured as a Gaussian process model;Providing a sample device feature of at least one device at a sample wafer position;Determining the device feature of at least one other device of the wafer depending on the provided wafer feature model.
wherein the system is further configured to control production of the devices depending on the determined device feature.

