Search device, search program, and plasma processing apparatus

Patent metadata

Field	Value
Publication number	US-2022291646-A1
Application number	US-201917272479-A
Country	US
Kind code	A1
Filing date	Dec 3, 2019
Priority date	Dec 3, 2019
Publication date	Sep 15, 2022
Grant date	—

Abstract

A parameter compression unit compresses first input parameter values so that a parameter restoration unit can restore the first input parameter values, and generates first compressed input parameter values in which the number of control parameters is reduced, a model learning unit learns a prediction model from learning data that is a set of the first compressed input parameter values and first output parameter values that processing results obtained by giving the first input parameter values, as a plurality of control parameters, to a processing device, and a processing condition search unit estimates a second compressed input parameter values corresponding to target output parameter values by using the prediction model.

First claim

1 . A search device configured to search for an input parameter value to be given to a plurality of control parameters set in a processing apparatus, so that a processing result of a predetermined process performed by the processing apparatus satisfies a target output parameter value, the search device comprising:
a processor; a memory; and a search program stored in the memory and configured to be executed by the processor to search for the input parameter value satisfying the target output parameter value, wherein the search program includes a parameter compression unit, a model learning unit, a processing condition search unit, a parameter restoration unit, and a convergence determination unit, the parameter compression unit compresses first input parameter values so that the parameter restoration unit is capable of restoring the first input parameter values, and generates first compressed input parameter values in which the number of control parameters is reduced, the model learning unit learns a prediction model from learning data that is a set of the first compressed input parameter values and first output parameter values that are processing results obtained by giving the first input parameter values, as the plurality of control parameters, to the processing device, the processing condition search unit estimates second compressed input parameter values corresponding to the target output parameter values by using the prediction model, the parameter restoration unit generates second input parameter values by adding control parameter values deleted by the parameter compression unit from the second compressed input parameter values, and the convergence determination unit determines whether second output parameter values, which are processing results obtained by giving the second input parameter values, as the plurality of control parameters, to the processing device, converges to a predetermined range of the target output parameter values.

2 . The search device according to claim 1 , wherein
when the convergence determination unit determines that the second output parameter values does not converge to the predetermined range of the target output parameter values, the search program updates the prediction model by adding set of the second input parameter values and the second output parameter values to a set of the first input parameter values, and the first output parameter values.

3 . The search device according to claim 1 , wherein
the predetermined processing includes a plurality of steps in which values given to the plurality of control parameters are different from each other, and the search program searches for values of the plurality of control parameters to be set in the plurality of steps as the input parameter values.

4 . The search device according to claim 1 , wherein
the processing condition search unit estimates a plurality of the second compressed input parameter values by using the prediction model.

5 . The search device according to claim 1 , wherein
the parameter compression unit deletes a part of the values of the control parameters of the first input parameter values such that the number of control parameters of the first input parameter values is equal to or less than the target number of parameters.

6 . The search device according to claim 5 , wherein
the parameter compression unit deletes a value of a control parameter which is not used or is a fixed value among the first input parameter values, and stores the deleted value of the control parameter.

7 . The search device according to claim 5 , wherein
the parameter compression unit deletes a value w of the second control parameter while leaving a value v of the first control parameter among the first input parameter values, and stores values of a coefficient a and an intercept b of w=av+b.

8 . The search device according to claim 7 , wherein
the value w of the second control parameter is proportional to the value v of the first control parameter, and the value v of the first control parameter and the value w of the second control parameter have a correlation coefficient larger than a predetermined threshold value.

9 . A search device configured to search for input parameter values to be given to a plurality of control parameters set in a processing apparatus, so that a processing result of a predetermined process performed by the processing apparatus satisfies target output parameter values, the search device comprising:
a processor; a memory; and a search program stored in the memory and configured to be executed by the processor to search for the input parameter value satisfying the target output parameter values, wherein the search program includes a model learning unit, a processing condition search unit, and a convergence determination unit, the model learning unit learns a prediction model from learning data that is a set of first input parameter values and first output parameter values that are processing results obtained by giving the first input parameter values, as the plurality of control parameters, to the processing device, the processing condition search unit estimates second input parameter value corresponding to the target output parameter values by using the prediction model, the convergence determination unit determines whether second output parameter values, which are processing results obtained by giving the second input parameter values, as the plurality of control parameters, to the processing device, converges to a predetermined range of the target output parameter values, and the processing condition search unit changes a value of a part of the control parameter of the first output parameter values and fixes a value of another control parameters to a value of a predetermined control parameters of the learning data to search for an approximate solution.

10 . The search device according to claim 9 , wherein
the processing condition search unit fixes a value of the another control parameter to a value of a control parameter of learning data that gives an optimum solution among the learning data.

11 . A search program configured to search for input parameter values to be given to a plurality of control parameters set in a processing device, so that a processing result of a predetermined process performed by the processing apparatus satisfies target output parameter values, the search program comprising:
a first step of compressing first input parameter values so that the first input parameter values can be restored, and generating first compressed input parameter values in which the number of control parameters is reduced; a second step of learning a prediction model from learning data that is a set of the first compressed input parameter values and first output parameter values that are processing results obtained by giving the first input parameter value, as the plurality of control parameters, to the processing device; a third step of estimating a second compressed input parameter values corresponding to the target output parameter values by using the prediction model; a fourth step of generating second input parameter values by adding a control parameter values deleted by the first step from the second compressed input parameter values, and a fifth step of determining whether second output parameter values, which are processing results obtained by giving the second input parameter values, as the plurality of control parameters, to the processing device, converges to a predetermined range of the target output parameter values.

12 . The search program according to claim 11 , wherein
in the fifth step, when it is determined that the

Assignees

• Hitachi High Tech Corp

Inventors

• Okuyama Yutaka
• Ohmori Takeshi

Classifications

• G05B13/0265 Primary

  the criterion being a learning criterion · CPC title

• H05H1/24

  Generating plasma {(nuclear fusion reactors G21B1/00; gas-filled discharge reactors H01J37/32)} · CPC title

• G05B13/048 Primary

  using a predictor · CPC title

• G05B13/042

  in which a parameter or coefficient is automatically adjusted to optimise the performance · CPC title

• G06N99/00

  Subject matter not provided for in other groups of this subclass · CPC title