Reduce Travel 30-70% With AI-Based Batch and Pick Path Optimization

Labor is the single largest operating cost in most DCs, and travel often accounts for half of all labor time, especially in order picking. Lucas travel and pick path optimization uses advanced mathematical models and artificial intelligence (AI) to reduce travel 30-70%. Warehouse picking optimization has allowed customers to more than double picking productivity and cut labor hours in half without making any changes to their warehouse layout or adding expensive automation or robotics.

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Travel Reduction Guide

How Does Travel & Pick Path Optimization Work?

Lucas uses order, inventory, and location information from WMS and other systems and Jennifer™ – the brain, voice and orchestration engine of the Lucas system – applies real-time optimization algorithms and warehouse picking strategies to create optimal work assignments. Jennifer™ then uses a virtual model of your facility to define an optimal pick sequence or travel path.

Jennifer™ prioritizes all available work assignments based on rules that you can configure and adjust throughout the day or week. Rules can be based on ship dates, routes, carriers, order types and more. Watch the on-demand demo → 

Rather than following a simple first-in-first-out batching method, Jennifer™ uses mathematical models to create optimized batches of pick lines and assigns them to pickers on-demand, as they request work. In contrast to typical WMS batching rules, the Lucas models weigh a variety of factors, including:

1) Order priority
2) Product locations
3) Product dimensions
4) Starting and ending points
5) Potential travel path
6) User permissions

Read more about intelligent batching →

After batches are created, Lucas applies multiple algorithms to determine an optimized path for the user to take through the warehouse to complete their work. The algorithms consider aisle directions (one-way aisles, for example), base item designations, and other factors to determine the most efficient pick path.

While Jennifer™ orchestrates and optimizes within picking zones, a DC can add robots for conveyance between pick zones or other staging locations. This can further reduce worker travel to and from fixed drop off or induction points. Likewise, Jennifer™ can be used to optimize the travel of robots for full pallet moves, both in inbound and outbound operations.

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As an added bonus for DCs processing higher volumes of ecommerce orders, the tool supports continuous order streaming or so-called waveless order release.

 

Get Started With These Helpful Resources

Three Steps to Creating a More Productive DC

This guide takes you through three steps that have helped hundreds of distribution centers worldwide increase productivity and throughput in their picking processes.

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AI based travel optimization

This 10 minute demo dives into the various components of our AI-based optimization tool – dynamic prioritization, path optimization and intelligent batching. Fill out the form and we will send you the demo.

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Warehouse Travel Reduction Guide

This guide looks in depth at how different approaches to implementing voice determine the magnitude of productivity gains any facility may achieve. Use the guidelines in this paper to estimate the potential results in your DC.

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We helped Baptist Health, a leading healthcare provider, double picking productivity.

“The previous average picking rate in the LUM area was 50-56 lines per hour (LPH). Today it is 100-110. That is a 100% improvement, and in bulk picking, the number is about 20 percent.”

Dale Adamson, AVP of Logistics and Distribution
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We helped Apex Tool Group, a leading manufacturer of hand and power tools, operate with 10% fewer man hours.

“You rarely implement a new system and have users tell you ‘It’s made my life so much easier!’ Making the processes better for associates makes them more productive. And that’s better for the business.”

Chris Rufa, Senior Director of Global Distribution
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