Clint Reiser points out in the linked article that a new revolution in supply chain analytics is occurring. There is new level of data detail, it’s coming at us faster, providing bigger patterns and better insights.
The detail isn’t just point-of-sale information, customer buying patterns, or fleet telematics. From Universal’s perspective, the combining of machine learning and machine vision into robust automated solutions for material handling processes previously thought as random is a unique source of this data.
The unique blend of having one foot in real-time physical processes and the other in logical logistics flow is providing real-time granularity that is a direct hit for insight breakthroughs that companies are longing for. Applications based on Neocortex, our 3D machine learning platform, are beginning to provide ongoing efficiency metrics associated with the physical characteristics of SKUs, cases, boxes, products, and parts. These can include inbound and outbound vendor efficiency, and metrics such as real-time packing densities.Tags: machine learning, machine vision, material handling, random data, supply chain, supply chain analytics, supply chain data