Warehouse optimization

Rationalizing (optimizing) a pharmaceutical picking warehouse is a task we frequently come across, e.g., when building a new warehouse and reorganizing one, when turnover increases or decreases, when discounts begin or end, or when the season begins or ends. There is no easy way to offer a good solution because of the large number of items, and there are many requirements that have to be met.

There are fundamental questions, such as:

  • How many storage units should be created?
  • What types of storage units are needed?

If the product range is known, these questions are easy to answer, but then the finer steps come into play:

  • Where should each product be placed?
  • How many pickers should be hired?
  • Based on the present turnover of the warehouse, what will be the picking time?

We help you answer these kinds of questions!

Optimization criteria:

1. Critical mass

  • A critical mass can be defined, and any goods exceeding this mass may only be placed on lower shelves.

2. Pickers

  • We can imagine the picking process as a conveyor belt, where the weakest link, i.e., the weakest picker determines the speed of the picking process. Provided that picking along individual sectors is not uniform, the rest of the sectors will experience downtime. Since the performance of the pickers is not identical, it is not enough to have identical picking tasks in the given sectors, because the weaker picker “slows down” the better pickers. The best course of action is to create picker groups and assign workers accordingly.

3. Storage space

  • When optimizing, the goal is to reach the lowest possible cost. The picking hour for storage units depends on their height, their type and their distance from the picking route. For this reason, storage unit types receive a multiplier representing the amount by which the picking cost for 1 item from the given storage unit is higher compared to the easiest storage unit to pick.

4. Exclusions

  • We might wish to avoid placing certain products or product groups next to one another. Perhaps we wish to organize the entire warehouse with separate product groups, and only optimize inside these. There may be a requirement for products with similar names not to be placed next to each other, e.g., items with the same first 4 (perhaps more or less) characters in their names.

Optimization in practice

One also has to adapt to changes in the marketplace – e.g., new products arrive, turnover increases for existing items or they are phased out of the product range – while the layout of the warehouse remains unchanged. Under the effects of these external factors, the initially optimal warehouse should (could) be modified in a few months. A choice of two methods is available:

  • Periodically (e.g., twice yearly), the warehouse is optimized according to the new state of the market.
  • We maintain the warehouse at an optimal level continuously. This means that the optimization algorithm can be told how many products it can move. E.g., we set the capacity to move 20 products each Friday, and at this time, we look for (possibly with the help of the StoreOpt system) the 20 products whose relocation would result in the greatest cost savings.

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