METHOD FOR CARRYING OUT MEASUREMENTS ON A VIRTUAL BASIS, DEVICE, AND COMPUTER READABLE MEDIUM

1 . A virtual metrology method, comprising:

acquiring production information of at least one production device; and

generating predictive data of measured products and unmeasured products using the production information and a prediction model, the predictive data comprising critical dimension data of the product.

2 . The virtual metrology method of claim 1 , further comprising:

obtaining metrology data of sampled unmeasured product;

determining whether a difference value between the metrology data and the predictive data is within a preset range; and

updating the prediction model using the production information and the metrology data when the difference value is not within the preset range.

3 . The virtual metrology method of claim 2 , wherein a process of updating the predict module comprises:

generating a user interface to display the preset range, and the difference value between the metrology data and the predictive data;

receiving an instruction to update the prediction model; and

reconstructing or adjusting the prediction model using the production information and the metrology data.

4 . The virtual metrology method of claim 1 , further comprising:

determining whether the prediction is successful; and

issuing a warning, if the prediction is not successful.

5 . The virtual metrology method of claim 1 , further comprising:

obtaining the production information and metrology data of the measured products; and

establishing the prediction model using the production information and the metrology data, the prediction model being a statistical model or a machine learning model.

6 . The virtual metrology method of claim 5 , wherein a process of obtaining the production information and metrology data of the measured products, comprises:

receiving the production information from at least one production device and the metrology data from at least one inspection device;

extracting, converting, and loading the production information and the metrology data; and

storing the production information and the metrology data in a database.

7 . The virtual metrology method of claim 6 , wherein the method further comprising:

comparing the metrology data of the same product from a plurality of the metrology devices at predetermined intervals, to correct the metrology data.

8 . The virtual metrology method of claim 1 , wherein the critical dimension data comprises thickness of a film and width of a metal line.

9 . A virtual metrology device, comprising:

at least one processor;

at least one storage device storing one or more programs, when executed by the processor, the one or more programs cause the processor to:

acquire production information of at least one production device;

generate predictive data of measured products and unmeasured products using the production information and a prediction model, the predictive data comprising critical dimension data of the product.

10 . The virtual metrology device of claim 9 , wherein the one or more programs cause the processor to:

obtain metrology data of sampled unmeasured product;

determine whether a difference value between the metrology data and the predictive data is within a preset range;

update the prediction model using the production information and the metrology data when the difference value is not within the preset range.

11 . The virtual metrology device of claim 10 , wherein a process of updating the predict module comprises:

generating a user interface to display the preset range, and the difference value between the metrology data and the predictive data;

receiving an instruction to update the prediction model; and

reconstructing or adjusting the prediction model using the production information and the metrology data.

12 . The virtual metrology device of claim 9 , wherein the one or more programs further cause the processor to:

determine whether the prediction is successful; and

issue a warning, if the prediction is not successful.

13 . The virtual metrology device of claim 9 , wherein the one or more programs further cause the processor to:

obtain the production information and metrology data of the measured products; and

establish the prediction model using the production information and the metrology data, the prediction model being a statistical model or a machine learning model.

14 . The virtual metrology device of claim 13 , wherein a process of obtaining the production information and metrology data of the measured products, comprises:

receiving the production information from at least one production device and the metrology data from at least one inspection device;

extracting, converting, and loading the production information and the metrology data;

storing the production information and the metrology data in an analysis database.

15 . The virtual metrology device of claim 9 , wherein the one or more programs further cause the processor to:

compare the metrology data of the same product from a plurality of the metrology devices at predetermined intervals, to correct the metrology data.

16 . The virtual metrology device of claim 9 , wherein the critical dimension data comprises thickness of a film and width of a metal line.

17 . A computer readable storage medium having stored thereon instructions that, when executed by at least one processor of a computing device, causes the processor to perform a virtual metrology method , wherein the method comprises:

acquiring production information of at least one production device;

generating predictive data of measured products and unmeasured products using the production information and a prediction model, the predictive data comprising critical dimension data of the product.

18 . The computer readable storage medium of claim 17 , wherein the method further comprising:

obtaining metrology data of sampled unmeasured product;

determining whether a difference value between the metrology data and the predictive data is within a preset range;

updating the prediction model using the production information and the metrology data when the difference value is not within the preset range.

19 . The computer readable storage medium of claim 18 , wherein a process of updating the predict module comprises:

generating a user interface to display the preset range, and the difference value between the metrology data and the predictive data;

receiving an instruction to update the prediction model;

reconstructing or adjusting the prediction model using the production information and the metrology data.

20 . The computer readable storage medium of claim 17 , wherein the method further comprising:

determining whether the prediction is successful;

issuing a warning, if the prediction is not successful.