JP2021174958A - 基板処理装置、基板処理方法、学習用データの生成方法、学習方法、学習装置、学習済モデルの生成方法、および、学習済モデル - Google Patents
基板処理装置、基板処理方法、学習用データの生成方法、学習方法、学習装置、学習済モデルの生成方法、および、学習済モデル Download PDFInfo
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Abstract
Description
20 制御装置
22 制御部
22a 基板情報取得部
22b 薬液処理条件情報取得部
24 記憶部
LM 学習済モデル
100 基板処理装置
130 薬液供給部
140 リンス液供給部
200 基板処理学習システム
300 学習用データ生成装置
400 学習装置
Claims (13)
- 硬化層の形成されたレジスト層を有する処理対象基板を回転可能に保持する基板保持部と、
前記処理対象基板に薬液を供給する薬液供給部と、
前記処理対象基板についての前記硬化層の厚さを示す硬化層厚さ情報または前記レジスト層に前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報を取得する基板情報取得部と、
前記基板情報に基づいて、学習済モデルから前記処理対象基板についての薬液処理条件を示す薬液処理条件情報を取得する薬液処理条件情報取得部と、
前記薬液処理条件情報取得部において取得された前記薬液処理条件情報に基づいて、前記処理対象基板を薬液で処理するように前記基板保持部および前記薬液供給部を制御する制御部と
を備え、
前記学習済モデルは、硬化層の形成されたレジスト層を有する学習対象基板について前記硬化層の厚さを示す硬化層厚さ情報または前記レジスト層に前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報と、前記学習対象基板を薬液で処理した条件を示す薬液処理条件情報と、前記学習対象基板を薬液で処理した結果を示す処理結果情報とが関連付けられた学習用データを機械学習することで構築される、基板処理装置。 - 前記学習済モデルを記憶する記憶部をさらに備える、請求項1に記載の基板処理装置。
- 前記処理対象基板および前記学習対象基板のそれぞれについて、前記硬化層厚さ情報は、前記硬化層の高さを示す硬化層高さ情報または前記硬化層の幅を示す硬化層幅情報を含む、請求項1または2に記載の基板処理装置。
- 前記処理対象基板および前記学習対象基板のそれぞれについて、前記薬液処理条件情報は、前記薬液の濃度、前記薬液の温度、前記薬液の供給量、前記薬液の吐出パターン、および、前記薬液を供給する際の基板の回転速度のいずれかを示す情報を含む、請求項1から3のいずれかに記載の基板処理装置。
- 前記薬液の濃度を示す情報は、前記薬液の濃度が時間とともに変化した濃度プロファイルを示す、請求項4に記載の基板処理装置。
- 前記薬液の温度を示す情報は、前記薬液の温度が時間とともに変化した温度プロファイルを示す、請求項4または5に記載の基板処理装置。
- 硬化層の形成されたレジスト層を有する処理対象基板を回転可能に保持するステップと、
前記処理対象基板についての前記硬化層の厚さを示す硬化層厚さ情報または前記レジスト層に前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報を取得するステップと、
前記基板情報に基づいて、学習済モデルから前記処理対象基板の薬液処理条件を示す薬液処理条件情報を取得するステップと、
前記薬液処理条件情報の薬液処理条件に従って前記処理対象基板を薬液で処理するステップと
を包含する、基板処理方法であって、
前記薬液処理条件情報を取得するステップにおいて、前記学習済モデルは、硬化層の形成されたレジスト層を有する学習対象基板について前記硬化層の厚さを示す硬化層厚さ情報または前記レジスト層に前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報と、前記学習対象基板に対して行われた薬液処理の条件を示す薬液処理条件情報と、前記学習対象基板に対して行われた薬液処理の結果を示す処理結果情報とが関連付けられた学習用データを機械学習することで構築される、基板処理方法。 - 硬化層の形成されたレジスト層を有する学習対象基板を処理する基板処理装置から出力される時系列データから、前記硬化層の厚さを示す硬化層厚さ情報または前記レジスト層に前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報を取得するステップと、
前記時系列データから、前記基板処理装置において前記学習対象基板を薬液で処理した条件を示す薬液処理条件情報を取得するステップと、
前記時系列データから、前記基板処理装置において前記学習対象基板を薬液で処理した結果を示す処理結果情報を取得するステップと、
前記学習対象基板について前記基板情報、前記薬液処理条件情報および前記処理結果情報を関連付けて学習用データとして記憶部に記憶するステップと
を包含する、学習用データの生成方法。 - 請求項8に記載の学習用データの生成方法にしたがって生成された学習用データを取得するステップと、
前記学習用データを学習プログラムに入力して前記学習用データを機械学習するステップと
を包含する、学習方法。 - 請求項8に記載の学習用データの生成方法にしたがって生成された学習用データを記憶する記憶部と、
前記学習用データを学習プログラムに入力して前記学習用データを機械学習する学習部と
を備える、学習装置。 - 請求項8に記載の学習用データの生成方法にしたがって生成された学習用データを取得するステップと、
前記学習用データを機械学習させることで構築された学習済モデルを生成するステップと
を包含する、学習済モデルの生成方法。 - 請求項8に記載の学習用データの生成方法にしたがって生成された学習用データを機械学習させることで構築された学習済モデル。
- 硬化層の形成されたレジスト層を有する基板を回転可能に保持する基板保持部と、
前記基板に薬液を供給する薬液供給部と、
硬化層厚さ情報またはイオン注入の条件を示すイオン注入条件情報を含む基板情報と、薬液処理の条件を示す薬液処理条件情報とが関連付けられた変換テーブルを記憶する記憶部と、
前記基板についての前記硬化層の厚さを示す硬化層厚さ情報または前記硬化層を形成したイオン注入の条件を示すイオン注入条件情報を含む基板情報を取得する基板情報取得部と、
前記基板情報に基づいて、前記変換テーブルを用いて前記基板についての薬液処理条件を示す薬液処理条件情報を取得する薬液処理条件情報取得部と、
前記薬液処理条件情報取得部において取得された前記薬液処理条件情報に基づいて前記基板を薬液で処理するように前記基板保持部および前記薬液供給部を制御する制御部と
を備える、基板処理装置。
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