Rating substrate support assemblies based on impedance circuit electron flow using machine learning
Abstract:
Methods and systems for rating a current substrate support assembly based on impedance circuit electron flow are provided. Data associated with an amount of radio frequency (RF) power flowed through an electrical component of a current substrate support assembly during a current testing process performed for the current substrate support assembly is provided as input to a trained machine learning model. One or more outputs of the trained machine learning model are obtained. A measurement value for an electron flow across an impedance circuit of the current substrate support assembly is extracted from the one or more outputs. In response to a determination that the extracted measurement value for the electron flow satisfies an electron flow criterion, a first quality rating is assigned to the current substrate support assembly.
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