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Slotting optimization is the process of deciding where each product should be stored in a warehouse so orders can be picked faster, safer, and at lower cost. It matters because a picker or robot may travel many kilometers per shift, and small location choices can greatly affect total time. Good slotting places high-demand items, heavy goods, and frequently paired products in positions that match the work flow of the building.

It connects math, data analysis, ergonomics, and operations engineering.

Key Facts

  • Pick frequency = number of picks for an item per time period.
  • Travel time = travel distance / average travel speed.
  • Expected travel cost = sum over items of pick frequency x distance x cost per meter.
  • Cube usage = used storage volume / available storage volume.
  • ABC slotting ranks items by activity, with A items picked most often and placed closest to fast pick zones.
  • Re-slotting benefit = current picking cost - optimized picking cost.

Vocabulary

Slotting optimization
Slotting optimization is the data-driven assignment of products to warehouse storage locations to reduce labor, travel, congestion, and handling cost.
Pick face
A pick face is the accessible storage location where a picker or robot retrieves units for customer orders.
ABC analysis
ABC analysis is a ranking method that groups items by activity or value so the most important items receive the best locations.
Affinity
Affinity is the tendency of two or more products to appear together in the same order.
Travel path
A travel path is the route taken by a picker, robot, or conveyor movement through the warehouse to complete work.

Common Mistakes to Avoid

  • Placing all fast movers at the very front, because this can create congestion and slow the whole aisle even though travel distance looks short.
  • Ignoring product size and weight, because a high-demand bulky item may waste prime space or create unsafe lifting if stored at the wrong height.
  • Using average demand only, because seasonal peaks and promotions can make yesterday's best slotting plan inefficient tomorrow.
  • Optimizing one item at a time, because orders are picked in groups and product affinity can matter as much as individual pick frequency.

Practice Questions

  1. 1 Item A is picked 180 times per day and is stored 42 m from the packing station. If moving it to a 12 m location does not change other work, how many meters of walking are saved per day?
  2. 2 A robot travels at 1.5 m/s. A slotting change reduces the average round trip distance for 600 picks from 50 m to 38 m. How many seconds of robot travel time are saved in one day?
  3. 3 A warehouse has one item that is very popular but large and heavy, and another item that is moderately popular but small and often ordered with many other products. Explain how a slotting optimizer might decide which item gets the closest pick face.