Eliminating Travel Within a Distribution Center Using Artificial Intelligence

Many DCs are experimenting with robotic solutions to reduce warehouse labor by eliminating travel. But what if there was an alternative that cost a fraction of the cost of robots or traditional automation?

Lucas has introduced an AI-based tool that reduces travel 30-70 percent in picking operations. Several customers using this new tool have more than doubled productivity in piece picking, while others have seen double-digit productivity gains in case picking. This software approach to travel reduction does not require any new automation systems or changes to warehouse layouts or storage systems. And the cost per user is a fraction of robotic solutions.

This paper reviews popular approaches to reducing travel in distribution center operations, and describes how AI-based optimization provides an alternative to capital-intensive robotic and automation solutions.