Applied Materials, Inc.
Chamber matching with neural networks in semiconductor equipment tools

Abstract:

A server trains a neural network by feeding a first set of input time-series data of one or more sensors of a first processing chamber that is within specification to the neural network to produce a corresponding first set of output time-series data. The server calculates a first error. The server feeds a second set of input time-series data from corresponding one or more sensors associated with a second processing chamber under test to the trained neural network to produce a corresponding second set of output time-series data. The server calculates a second error. Responsive to the difference between a second error between the second set of input time-series data and the corresponding second set of output time-series data and a first error between the first set of input time-series data and the corresponding first set of output time-series data being equal to or exceeding a threshold amount, the server declares that the second processing chamber under test mismatches the first processing chamber that is within specifications.