Abstract: Techniques for computing optimal range of unit product value for products having insufficient product consumption data are described. In an example, a plurality of identifiers corresponding to names of a plurality of products may be determined. Based on the plurality of identifiers, two or more clusters may be generated. Within each cluster, a first identifier associated with a product having insufficient product consumption data and a second identifier associated with a product having sufficient product consumption data is determined. Further, based on demand curve data for the product associated with the second identifier, an optimal range of a unit product value for the product associated with the first identifier is computed.

Abstract: Approaches for product consumption data clustering are described. In an example implementation, cumulative product consumption data of each product of plurality of products, including at least three data points indicative of varying cumulative product consumption quantities with respect to varying unit product values, is obtained and re-scaled by normalizing varying cumulative product consumption quantities and varying unit product values to be within first predefined numerical range and second predefined numerical range, respectively. Re-scaled cumulative product consumption data of each product is clustered, by cluster generation module, into plurality of clusters based on mapping of re-scaled cumulative product consumption data with respect to plurality of non-overlapping regions in a predefined cluster determination plot generated by processor.

Abstract: Systems and methods to fuse aviation-related data systems for comprehensive aircraft system health monitoring are provided. One example method includes obtaining, by one or more computing devices, fault data indicative of a plurality of fault indications provided by a first plurality of components of an aircraft. The method includes obtaining, by the one or more computing devices, condition indicators describing the respective operational conditions of a second plurality of components of the aircraft. The method includes fusing, by the one or more computing devices, the fault data with the condition indicators to form a comprehensive data set. The method includes identifying, by the one or more computing devices, one or more causes of the plurality of fault conditions based at least in part on the comprehensive data set. One example system includes a data fuser, a cause identifier, and an alert generator.

Abstract: Systems and methods to fuse aviation-related data systems for comprehensive aircraft system health monitoring are provided. One example method includes obtaining, by one or more computing devices, fault data indicative of a plurality of fault indications provided by a first plurality of components of an aircraft. The method includes obtaining, by the one or more computing devices, condition indicators describing the respective operational conditions of a second plurality of components of the aircraft. The method includes fusing, by the one or more computing devices, the fault data with the condition indicators to form a comprehensive data set. The method includes identifying, by the one or more computing devices, one or more causes of the plurality of fault conditions based at least in part on the comprehensive data set. One example system includes a data fuser, a cause identifier, and an alert generator.