Warehouse layout optimization – Part II: pick path & product location
In the first part of this article, we talked about the possible rack arrangements in the storage space in order to optimize travel time within the warehouse. But the arrangement of the racks is only one part of the solution for warehouse layout optimization. We also need to analyze the picking route options and your storage allocation policy and select the combination of the arrangement-picking route that will yield the minimum travel time. This will be the subject of the second part of this two-part series.
Picking path and warehouse layout optimization
Once the layout is defined, the next step is to set out the traffic flow within the layout. Picking path optimization is the process of finding the fastest way to navigate the warehouse in order to pick products quickly, accurately, and efficiently. Many studies have been done looking at different algorithms to define the best picking path, but none of them guarantee success in all picking scenarios.
Figure 4 illustrates the four most used picking path policies for an order whose items are in the blue spaces. For the analysis, let’s assume a rectangular layout and that each rack is 10 ft. wide, so the total storage area is 140×140 ft.
S-shape route: In the S-shape policy, the path followed by the order pickers is in the shape of an S. This implies that any aisle containing at least one pick is traveled entirely by the order picker. Aisles without picks are not entered and the order picker returns to the drop-off location (depot) from the last visited aisle. The total distance the forklift has to travel will be 1,020 ft.
Return route: In the return policy, an aisle is entered and exited from the same end. Only aisles with picks are entered. If most of the pick locations are at one end of each aisle, this method can be quite effective. For the picking in the example, the total distance traveled will be 1,600 ft.
Mid-Point route: In the mid-point policy, the warehouse is divided into two halves. Picks from the bottom half are retrieved from the bottom cross-aisle, while picks from the top half are retrieved from the top cross-aisle. If the number of picks per aisle is small, this policy provides better results than the S-shape policy. The total distance traveled will also b3 1,020 ft.
Largest Gap route: In the largest gap policy, order pickers avoid the largest gap during the picking operation. When there is a pick-up location in an aisle, there can be three gaps: (1) the distance between the top cross-aisle and the first pick location in the aisle, (2) the distance between two middle pick locations, and (3) the distance between the bottom cross-aisle and the last pick location. The largest of these three gaps is avoided. In this picking example, the distance traveled will be 1,000 ft.
However, if there had been a cross aisle in the middle of the warehouse, the travel time for the S-Shape picking path would have been reduced to 870 ft. Similar reductions would occur with the rest of the paths.
If your WMS can show you the location of the products to pick, an experienced picker can select the method that will yield the minimum travel time for each order.
Product storage allocation and warehouse layout optimization
The third element to consider for warehouse layout optimization is the default location of the products. For any picking optimization method to be successful, you need to have tagged your warehouse locations down to the bin level; otherwise, there is no way to define a picking path. In addition, where you store products has a great impact on the route of travel. You can watch this video on how to label your bins.
We also recently discussed potential product allocation strategies in our explanation of the put-away process. In that article, we concluded that the Pareto principle is the most used strategy for product allocation. This rule (also known as the 80/20 rule) refers to the movement of inventory in warehouses. This thumb rule states that approximately 80% of the activity in the warehouse comes from 20% of the products, which are frequently transferred inside the building. Next 15% of the activity is derived from the 30% stock-keeping units (SKUs), whose mobility rate is defined as the average. Finally, 5% of the activity comes from 50% of the inventory, which is stored gradually. By separating the fast, medium, and slow-moving products within the plant and increasing access to products requiring the highest activity, throughput can be significantly increased.
Imagine, in the picking paths options in figure 3, that the top Pareto items are stored in the aisle close to the starting point. Instead of having sparse picking bins, you will have a concentration of items to be picked around the bottom of the first two aisles.
Example of picking time for different layouts
G. Dukic et al. conducted a simulation to illustrate the relationship between warehouse layout optimization and picking time. The analysis was carried out with the following variables:
- Two order sizes, one relatively small with 10 picks per order, and one large with 30 picks per order.
- Three arrangements of racks
- S-shape picking policy
- Picking items randomly distributed throughout the warehouse
The results are summarized below. The conclusion is that the U-shape layout with cross aisles gives the best travel time.
Each distribution business has its own peculiarities and will require different arrangements, picking path policies and product storage policy consistent with them. The idea of these two articles is to motivate that warehouse layout optimization is very complex and should not be taken lightly. I have given the topics to consider and the different options for each of them. I hope they will be useful when you decide to change your existing layout or if you are starting a new facility.
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You can also watch related video on the subject in our YouTube channel