Mckesson Corporation

Anshul Kumar

Jacob Hookom

Duy Tran

Hemanth Bandi

Dan Li

Devang Dhaka

Whitney Ann Gregory

Bethann Maynard

Provided are methods, systems, and apparatuses for improving supply chain management interfaces and functionality. A frequency of occurrence for each unique combination of a use attribute and a product attribute for various supplies may be determined. A frequency table containing each unique combination may be generated as well as one or more association rules. A level of confidence and a level of lift may be determined for each of the one or more association rules, both of which may be used to generate a score for each unique combination that may be used to rank each unique combination. The ranked unique combinations may then be provided to a supply chain management interface and a database.

Methods and systems for association rule mining

Described herein are methods, systems, and apparatuses for storage analysis and management using computer vision techniques. An imaging device may capture a series of images of a plurality of containers. The series of images may be analyzed by a classification model to determine a current capacity of each container. When the classification model determines that a current capacity of a container(s) satisfies a threshold(s), at least one remedial action may be performed.

Methods, systems, and apparatuses for storage analysis and management

Provided are methods, systems, and apparatuses for improving supply chain management interfaces and functionality. The supply chain management interfaces may provide visualizations of one or more standardization constructs associated with an organization and locations thereof. A standardization construct may be generated using supply chain records associated with the organization and locations thereof. The visualizations of the one or more standardization constructs may be adjusted at a user interface. The adjusted one or more standardization constructs may be indicative of ways in which the one or more standardization constructs may be improved.

Methods and systems for supply chain analytics

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Glen Allen, VA, United States of America

Anshul Kumar