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Lucas began pivoting toward becoming an optimization company in 2017 when it introduced dynamic task prioritization and pick-pathoptimization. Once the work has batched, the system works on pathoptimization. But batching and pathoptimization work together for increased synergies.
The solution creates optimized batches of work for assignment to associates, develops optimal pick paths, and dynamically prioritizes warehouse tasks. The solution creates optimized batches of work based on criteria such as product dimensions, locations, pick path start and end points, and more.
In most cases, a WMS follows basic logic and location sequence pick paths in allocating work. But it is not looking at batch and pathoptimization without robots.
Newer execution software can support alternative picking processes for different order profiles, dynamically optimize picking assignments, and adapt as new requirements emerge. One practical example of dynamic is AI-based batching and pick pathoptimization to reduce travel. Inventory and Labor Planning.
Similarly, the ideal travel path calculation is not a simple measure of distance, but must also factor in variables like the cost (in time) of turning around a cart or jack, directional aisle restrictions, and zone sequencing. Furthermore, this travel path must be used to calculate the optimized batch in the first place.
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.
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