State prediction apparatus and semiconductor manufacturing apparatus

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.

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.