In a storage region where multiple SKUs are kept, the key decision variable in deep-lane storage is D, the number of rows allocated. Since each load has a depth of y, the lane depth becomes Y = yD. Different choices of D will lead to different levels of cube utilization. Because the space taken up by the items themselves is already known, cube utilization can be calculated once the total space is defined. This total space includes the actual item space, any honeycomb loss (unused lane depth), and the additional space required for access such as down aisles.
Deep-lane storage design, especially in the context of lane depth optimisation (Y = yD), cube utilisation (CU), and the effect of honeycomb loss and access aisle space for making layout decisions for cold storage or other warehouse settings.
| Symbol | Meaning |
|---|---|
| D | Number of rows in the region |
| y | Unit-load depth |
| Y = yD | Lane depth |
| x | Unit-load width |
| z | Unit-load height |
| H | Stack height in number of levels |
| M_i | Max number of units of SKU i |
| M | Total number of units of all SKUs |
| N | Number of SKUs |
| L(D) | Number of lanes for given D |
| A | Width of down aisle |
| X | Width of storage region (row length) |
| Z | Total height of the storage region |
| TS(D) | Total 3D storage volume for D |
| TA(D) | Total 2D floor area for D |
Cold storage calculations inventory management
EFFECTIVE DESIGN INSIGHTS
What You’re Optimising
You’re adjusting D to maximize cube utilization:
Trade-offs
COLD CHAIN STORAGE
If you’re dealing with, say, cream cheese tubs or frozen meat cartons, you’d plug in: