Chamber matching with neural networks in semiconductor equipment tools
US-2020243359-A1 · Jul 30, 2020 · US
US12050455B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12050455-B2 |
| Application number | US-201916533273-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 6, 2019 |
| Priority date | Aug 21, 2018 |
| Publication date | Jul 30, 2024 |
| Grant date | Jul 30, 2024 |
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Provided is a state prediction apparatus that predicts a state of the plasma processing apparatus, a first set of features that indicates the state of the plasma processing apparatus is determined based on monitored data of the plasma processing apparatus in a normal state, a second set of features that indicates the state of the plasma processing apparatus is determined based on monitored data of the plasma processing apparatus, the features in the second set are calculated by using the features in the first set, a model that predicts the state of the plasma processing apparatus is generated by using a subset of the first set of features, which is composed of the same kind of features selected in descending order of the calculated features in the second set, and the state of the plasma processing apparatus is predicted by using the generated model.
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What is claimed is: 1. A state prediction apparatus that predicts a state of a plasma processing apparatus, comprising: a computer configured to acquire training data comprising a data group for a plurality of samples, the data group including extracted feature data obtained in a normal etching apparatus state; calculate a first set of features that indicates a state of the plasma processing apparatus based on the acquired training data of the plasma processing apparatus when the state of the plasma processing apparatus is a normal state; acquire a second set of features comprising testing data for detecting an abnormality; standardize the features in the second set using the features in the first set, wherein the standardized features of the second set comprise a value indicating a degree of deviation of the plasma processing apparatus from the normal state in the second set of features; create a ranking of the features of the standardized features of the second set; select a number in descending order of the ranked features; create a model that predicts the state of the plasma processing apparatus using a subset of the first set of features, which is composed of a same kind of features selected in descending order of the standardized features in the second set; and predict the state of the plasma processing apparatus by using the generated model. 2. The state prediction apparatus according to claim 1 , wherein the generated model is regenerated each time the state of the plasma processing apparatus is predicted. 3. The state prediction apparatus according to claim 1 , wherein the standardized features in the second set are each a value obtained by dividing a value, which is obtained by subtracting an average value of the features in the first set in a plurality of plasma processings from the features in the second set, by a standard deviation of the features in the first set in the plurality of plasma processings. 4. A semiconductor manufacturing apparatus, comprising: a processing chamber in which a sample is processed; a transfer chamber that transfers the sample to the processing chamber and is connected to the processing chamber; and a control device comprising a computer configured to acquire training data comprising a data group for a plurality of samples, the data group including feature data extracted in a normal etching apparatus state; calculate a first set of features that indicates a state of the plasma processing apparatus based on the acquired training data of the plasma processing apparatus when the state of the plasma processing apparatus is a normal state; acquire a second set of features comprising testing data for detecting an abnormality; standardize the features in the second set using the features in the first set, wherein the standardized features of the second set comprise a value indicating a degree of deviation of the plasma processing apparatus from the normal state in the second set of features; create a ranking of the features of the standardized features of the second set; select a number in descending order of the ranked features; create a model that predicts the state of the plasma processing apparatus using a subset of the first set of features, which is composed of a same kind of features selected in descending order of the standardized features in the second set; and predict the state of the plasma processing apparatus by using the generated model. 5. The semiconductor manufacturing apparatus according to claim 4 , wherein any position in the semiconductor manufacturing apparatus is the processing chamber or the transfer chamber. 6. The semiconductor manufacturing apparatus according to claim 5 , wherein the standardized features in the second set are each a value obtained by dividing a value, which is obtained by subtracting an average value of the features in the first set in a plurality of processings from the features in the second set, by a standard deviation of the features in the first set in the plurality of processings. 7. A semiconductor manufacturing apparatus comprising: a processing chamber in which a sample is processed and a transfer chamber which transfers the sample to the processing chamber and is connected to the processing chamber; and a state prediction apparatus comprising a computer configured to acquire training data comprising a data group for a plurality of samples, the data group including feature data extracted in a normal etching apparatus state; calculate a first set of features that indicates a state of the plasma processing apparatus based on the acquired training data of the plasma processing apparatus when the state of the plasma processing apparatus is a normal state; acquire a second set of features comprising testing data for detecting an abnormality; standardize the features in the second set using the features in the first set, wherein the standardized features of the second set comprise a value indicating a degree of deviation of the plasma processing apparatus from the normal state in the second set of features; create a ranking of the features of the standardized features of the second set; select a number in descending order of the ranked features; create a model that predicts the state of the plasma processing apparatus using a subset of the first set of features, which is composed of a same kind of features selected in descending order of the standardized features in the second set; and predict the state of the plasma processing apparatus by using the generated model. 8. The semiconductor manufacturing apparatus according to claim 7 , wherein any position in the semiconductor manufacturing apparatus is the processing chamber or the transfer chamber. 9. The semiconductor manufacturing apparatus according to claim 8 , wherein the standardized features in the second set are each a value obtained by dividing a value, which is obtained by subtracting an average value of the features in the first set in a plurality of processings from the features in the second set, by a standard deviation of the features in the first set in the plurality of processings.
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