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.
DWO uses mathematical models to create optimized batches of pick lines and assigns them to pickers on-demand, as they request work. The models account for priority, location, product dimensions, and other factors. In contrast to typical WMS batching rules, DWO batches orders by weighing a variety of complex factors, which are built into the models:
1) Order priority
2) Product locations
3) Product dimensions
4) Starting and ending points
5) Potential travel path
6) User permissions
DWO applies multiple algorithms to determine an optimized path for the user to take through the warehouse to complete their work. The algorithms consider multiple factors, not just travel distance, to determine the most efficient pick path.
1) Travel Distance
2) Zone Sequencing
3) User start/end points
4) Cost of moves (e.g., turning around)
5) Directional aisle restrictions
Warehouse management 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.
The images above 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%. Click here to learn more about batching with DWO →
1) Greater than 120% increase in lines per hours
2) 50% reduction in labor hours
3) Increased throughput with reduced labor
4) Simplified work release and management
5) Improved on-time shipments
Interested in seeing what kinds of improvements Dynamic Work Optimization could deliver in your warehouse? Fill out the form to request a demo and speak directly with someone on the Lucas team. Ask us about running a DWO simulation in your facility to see how much travel time you could save.
Watch our brief overview to learn how Lucas DWO uses advanced mathematical models and artificial intelligence to reduce DC travel 30-70%.
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