Abstract: This application relates to techniques for recommending content to a user of a content distribution system. A server device can generate recommendations as part of a user interface for the content distribution system. The server device can be configured to: calculate a trend score for each of a plurality of digital assets managed by a content distribution system, calculate a recommendation score for a subset of digital assets that are not installed on a client device of a target user, calculate a breakout score for a subset of digital assets managed by the content distribution system each having a cumulative number of downloads below a threshold value, rank the digital assets according to the trend scores, the recommendation scores, or the breakout scores, and generate a visual representation of one or more digital assets to recommend to the user based on the ranking.

Abstract: This application relates to techniques for recommending content to a user of a content distribution system. A server device can generate recommendations as part of a user interface for the content distribution system. The server device can be configured to: calculate a trend score for each of a plurality of digital assets managed by a content distribution system, calculate a recommendation score for a subset of digital assets that are not installed on a client device of a target user, calculate a breakout score for a subset of digital assets managed by the content distribution system each having a cumulative number of downloads below a threshold value, rank the digital assets according to the trend scores, the recommendation scores, or the breakout scores, and generate a visual representation of one or more digital assets to recommend to the user based on the ranking.

Abstract: This application relates to techniques for recommending content to a user of a content distribution system. A server device can generate recommendations as part of a user interface for the content distribution system. The server device can be configured to: calculate a trend score for each of a plurality of digital assets managed by a content distribution system, calculate a recommendation score for a subset of digital assets that are not installed on a client device of a target user, calculate a breakout score for a subset of digital assets managed by the content distribution system each having a cumulative number of downloads below a threshold value, rank the digital assets according to the trend scores, the recommendation scores, or the breakout scores, and generate a visual representation of one or more digital assets to recommend to the user based on the ranking.

Abstract: A method for assessing health status of a processing chamber is provided. The method includes executing a recipe. The method also includes receiving processing data from a set of sensors during execution of the recipe. The method further includes analyzing the processing data utilizing a set of multi-variate predictive models. The method yet also includes generating a set of component wear data values. The method yet further includes comparing the set of component wear data values against a set of useful life threshold ranges. The method moreover includes generating a warning if the set of component wear data values is outside of the set of useful life threshold ranges.

Abstract: A method for predicting etch rate uniformity for qualifying health status of a processing chamber during substrate processing of substrates is provided. The method includes executing a recipe and receiving processing data from a first set of sensors. The method further includes analyzing the processing data utilizing a subsystem health check predictive model to determine calculated data, which includes at least one of etch rate data and uniformity data. The subsystem health check predictive model is constructed by correlating measurement data from a set of film substrates with processing data collected during analogous processing of a set of non-film substrates. The method yet also includes performing a comparison of the calculated data against a set of control limits as defined by the subsystem health check predictive model. The method yet further includes generating a warning if the calculated data is outside of the set of control limits.

Abstract: A method for assessing health status of a processing chamber is provided. The method includes executing a recipe. The method also includes receiving processing data from a set of sensors during execution of the recipe. The method further includes analyzing the processing data utilizing a set of multi-variate predictive models. The method yet also includes generating a set of component wear data values. The method yet further includes comparing the set of component wear data values against a set of useful life threshold ranges. The method moreover includes generating a warning if the set of component wear data values is outside of the set of useful life threshold ranges.

Abstract: A method for predicting etch rate uniformity for qualifying health status of a processing chamber during substrate processing of substrates is provided. The method includes executing a recipe and receiving processing data from a first set of sensors. The method further includes analyzing the processing data utilizing a subsystem health check predictive model to determine calculated data, which includes at least one of etch rate data and uniformity data. The subsystem health check predictive model is constructed by correlating measurement data from a set of film substrates with processing data collected during analogous processing of a set of non-film substrates. The method yet also includes performing a comparison of the calculated data against a set of control limits as defined by the subsystem health check predictive model. The method yet further includes generating a warning if the calculated data is outside of the set of control limits.