Dynamic Work Optimization
Reduce Travel 30-70% And Double Productivity Without Automation
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 Dynamic Work Optimization (DWO) uses advanced mathematical models and artificial intelligence (AI) to reduce travel 30-70%. Customers using DWO have more than doubled picking productivity and cut labor hours in half without making any changes to their warehouse layout or adding expensive automation or robotics.
Watch this short animation for an overview of DWO
How DWO Works
Dynamic Work Optimization is an advanced module within Lucas Engage that dynamically manages priority, maximizes pick density, and optimizes travel paths in picking and other travel-intensive warehouse processes.
DWO uses order, inventory, and location information from WMS and other systems and applies real-time optimization algorithms to create work assignments. It then uses a virtual model of your facility to define an optimal pick sequence or travel path. Unlike rule-based batch and pick-path strategies, our AI-based optimization technology dramatically increases pick density and reduces travel.
Among other benefits, Lucas’ DWO also provides on-demand work creation to support waveless picking (sometimes called “order streaming”) by allowing you to reprioritize, batch, and release work as new orders are received. The tool includes three components – Dynamic Prioritization, Batch Optimization, and Path Optimization – that strike a balance between automation and configurability. It provides all the benefits of AI while allowing your managers to intervene so they can deal with unforeseen circumstances that may arise in your operations.
As new orders are received, DWO dynamically sorts work by priority, based on rules that managers can configure and adjust throughout the day or week. Front-line managers can also change the priority of work throughout the day, at any point up until it is assigned to a user.
When a user requests work in a picking area, DWO applies multiple algorithms to all available orders in the system to create optimized batches. The tool considers shipping time, proximity, and other variables:
1) Order priority
2) Product locations
3) Product dimensions
4) Starting and ending points
5) Potential travel path
6) User permissions
DWO Compared To WMS Batching
The images below demonstrate the difference between Lucas DWO and the simplistic first in, first out (FIFO) batching method provided by most WMS or ERP systems.
Lucas DWO Batch optimization reduces travel time between 15-30%.
Whereas other systems have static rules that batch work orders as they are imported, because it executes batching on-demand, the DWO batch optimization component uses dynamic rules that can shift throughout the day.
For example, you can set the system to focus more on pick density early in the day, when there is plenty of time before the first orders are due at the shipping dock. Then the system can automatically transition to optimize for priority, as route cut-off times are approaching, based on the schedule for that day or week.
Traditional FIFO Batching
Intelligent Batching With Lucas
Lucas DWO takes into account the pick locations and batches together orders 1 & 6 because there is only one pick (highlighted in green) that requires extra travel.
DWO defines the most efficient route through the warehouse for a user to complete a given work assignment, rather than following a strict aisle-bay location sequence. The DWO algorithms take account of multiple factors to determine the ideal path. Factors may include:
1) Travel Distance
2) Zone sequencing
3) User start/end points
4) Cost of moves (e.g., turning around)
5) Directional aisle restrictions
DWO Compared To WMS Pick Paths
The short simulation video below shows intelligent paths directed by Lucas DWO, including the comparison (in the bottom right) to the travel required to make the same picks in warehouse sequence.
Based on dozens of real-world cases, DWO reduces travel 30-70% in a range of picking scenarios, including case pick to pallet and less-than-case picking to carts. Actual customer results include:
50% reduction in labor hours.
Increased throughput with reduced labor
Greater than 120% increase in lines per hour
Improved on-time shipment
Simplified work release and management
Request A Demo
Interested in seeing what kinds of improvements Dynamic Work Optimization could deliver in your warehouse? Fill out the form below to request a demo and speak directly with someone on the Lucas team.