Abstract: Methods and systems include receiving a product attribute that identifies a product. A first component attribute and a second component attribute are received. The first component attribute identifies a first component included in the product and the second component attribute identifies a second component included in the product. The methods and systems further includes receiving first manufacturing data associated with the first component and second manufacturing data associated with the second component, applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, applying a set of pairing rules to the pairing data, determining one or more actions from the application of the set of pairing rules to the pairing data, and performing the one or more actions.

Abstract: A method of augmenting a reliability model of products including a particular product in use by an end user. The particular product includes a first component and a second component each having component attributes. The method also includes receiving first data of the first component and second data of the second component generated during use of the particular product by the end user and comparing the first data to the second data. The method also includes identifying a measure of compatibility between the components, determining pairing data based on the measure of compatibility, and applying a set of pairing rules to the pairing data. The method further includes modifying the reliability model based at least in part on the application of the pairing rules to the pairing data to generate an augmented reliability model and initiating one or more actions in association with the augmented reliability model.

Abstract: A method of augmenting a reliability model of products including a particular product in use by an end user. The particular product includes a first component and a second component each having component attributes. The method also includes receiving first data of the first component and second data of the second component generated during use of the particular product by the end user and comparing the first data to the second data. The method also includes identifying a measure of compatibility between the components, determining pairing data based on the measure of compatibility, and applying a set of pairing rules to the pairing data. The method further includes modifying the reliability model based at least in part on the application of the pairing rules to the pairing data to generate an augmented reliability model and initiating one or more actions in association with the augmented reliability model.

Abstract: Methods and systems include receiving a product attribute that identifies a product. A first component attribute and a second component attribute are received. The first component attribute identifies a first component included in the product and the second component attribute identifies a second component included in the product. The methods and systems further includes receiving first manufacturing data associated with the first component and second manufacturing data associated with the second component, applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, applying a set of pairing rules to the pairing data, determining one or more actions from the application of the set of pairing rules to the pairing data, and performing the one or more actions.

Abstract: A method of augmenting a reliability model for a manufactured product includes receiving a product attribute identifying a product, receiving a first component attribute and a second component attribute, and receiving first manufacturing data and second manufacturing data, the first manufacturing data comprising manufacturing data associated with the first component and the second manufacturing data comprising manufacturing data associated with the second component. The method can include applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, obtaining a reliability model of products including the product, augmenting the reliability model based on the pairing data, and performing one or more actions with the augmented reliability model.

Abstract: Methods and systems include receiving a product attribute that identifies a product. A first component attribute and a second component attribute are received The first component attribute identifies a first component included in the product and the second component attribute identifies a second component included in the product. The methods and systems further includes receiving first manufacturing data associated with the first component and second manufacturing data associated with the second component, applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, applying a set of pairing rules to the pairing data, determining one or more actions from the application of the set of pairing rules to the pairing data, and performing the one or more actions.

Abstract: Embodiments describe a method of augmenting a reliability model for a manufactured product. The method includes receiving a product attribute identifying a product, receiving a first component attribute and a second component attribute, and receiving first manufacturing data and second manufacturing data, the first manufacturing data comprising manufacturing data associated with the first component and the second manufacturing data comprising manufacturing data associated with the second component. The method can include applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, obtaining a reliability model of products including the product, augmenting the reliability model based on the pairing data, and performing one or more actions with the augmented reliability model.

Abstract: Embodiments describe a method of manufacture including receiving a product attribute identifying a product, and receiving a first component attribute and a second component attribute, the first component attribute identifying a first component included in the product and the second component attribute identifying a second component included in the product. The method further includes receiving first manufacturing data associated with the first component and second manufacturing data associated with the second component, applying a set of compatibility rules to the first manufacturing data and the second manufacturing data, determining pairing data from the application of the set of compatibility rules to the first manufacturing data and the second manufacturing data, applying a set of pairing rules to the pairing data, determining one or more actions from the application of the set of pairing rules to the pairing data, and performing the one or more actions.

Abstract: Disclosed are methods, systems and computer program products where an item may or may not be determined as counterfeit based on result(s) of a comparison between test data for the item, and test data for items that are associated with manufacturing data in the cluster that is most likely to include manufacturing data that is associated with attribute data obtained for the item. In some embodiments, such methods, systems and computer program products may allow automated, universal non-destructive, and/or non-invasive detection of counterfeit electronic items. In some embodiments, counterfeit detection may be integrated into existing supply chains, including high volume manufacturing supply chains, and may be performed for a large variety of items without a need for a major adjustment to manufacturing. However, the counterfeit detection in some embodiments may not necessarily be integrated into manufacturing and may occur at any time, even when an item is in use.

Abstract: Disclosed are methods, systems and computer program products where an item may or may not be determined as counterfeit based on result(s) of a comparison between test data for the item, and test data for items that are associated with manufacturing data in the cluster that is most likely to include manufacturing data that is associated with attribute data obtained for the item. In some embodiments, such methods, systems and computer program products may allow automated, universal non-destructive, and/or non-invasive detection of counterfeit electronic items. In some embodiments, counterfeit detection may be integrated into existing supply chains, including high volume manufacturing supply chains, and may be performed for a large variety of items without a need for a major adjustment to manufacturing. However, the counterfeit detection in some embodiments may not necessarily be integrated into manufacturing and may occur at any time, even when an item is in use.

Abstract: Disclosed are methods, systems and computer program products for concluding whether or not there is a correlation between a set of manufacturing condition(s) and performance of in-field end user devices. Also disclosed are methods, systems and computer program products for concluding whether or not there is an inconsistency in in-field end user devices data and/or manufacturing data associated with electronic elements included in end-user devices. In one example, a method includes analyzing received in-field data and/or data computed based on received in-field data, in order to determine whether or not there is a statistically significant difference in in-field performance between end-user devices including elements from a first population and end-user devices including elements from a second population, where manufacturing of the first population corresponds to a set of one or more manufacturing conditions, but manufacturing of the second population does not correspond to the set.