When a user requests work in a picking area, Lucas applies multiple algorithms to all available orders in the system to create optimized batches. The tool considers shipping time, proximity, and other variables.
Lucas Insight is a data reporting and analytics tool that combines current operational data with historical data to improve analysis, planning, and decision-making across a network of DCs.
Using AMRs as take-away or transport systems will eliminate some worker travel, but warehouses will still need to optimize pick rates and minimize worker travel within picking areas.
Our analysis shows that many DCs will not be able to justify the up front investment costs for picking AMRs, even when doubling productivity. For those facilities, lower-cost approaches to reducing travel can deliver a bigger, faster ROI.
Order picking bucket brigades are a way of organizing workers and orchestrating work in a warehouse pick module. The bucket brigade process balances workflow and distributes work evenly amongst the pickers, maximizing productivity and throughput. Top-performing bucket brigades typically use voice picking technology.
Two stage picking is a popular strategy for improving the picking efficiency for slow-moving items in a warehouse or distribution center. This short animation illustrates a simplified two-stage picking process in a DC using Lucas Move applications featuring Jennifer Voice.
Stores will need to employ the same process and operations best practices that have been used for years in DCs. Those best practices can help retailers improve margins and profits on local fulfillment of ecommerce orders.
The current ecommerce surge is accelerating the evolution of last mile fulfillment and modular micro-fulfillment technology will co-exist with AI-optimized manual processes in stores, DCs, and local fulfillment centers to help get orders out the door faster and with more accuracy.
For warehouses picking smaller orders into totes or cartons, the order totes can be passed from zone to zone to complete picking (pick and pass). But for DCs picking larger orders by zone, it is typically more efficient to consolidate the items for the order after picking across all zones (pick and merge).
In order to become proactive instead of reactive we need predictive and prescriptive analytics, through machine learning, artificial intelligence and data science.