Warehouses Optimize Drivein Rack Picking for Efficiency FIFO

Drive-in racks have become a favored solution in modern warehouse management due to their high-density storage capabilities. However, their unique structure presents significant challenges for picking operations. When faced with varying pallet quantities and complex rack layouts, designing a strategy that balances picking efficiency with inventory management principles like First-In-First-Out (FIFO) becomes critical for warehouse operators.

The storage logic of drive-in racks typically follows either Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) principles, depending on aisle design and operational processes. The core challenges include:

• Depth-related picking difficulty: Items stored deeper within the rack require more time and effort to retrieve.
• Quantity variability: A single rack may contain both full pallets (e.g., 1000kg) and partial pallets (e.g., 500kg).
• Strategy conflicts: Traditional quantity-based approaches (prioritizing either full or partial pallets) often contradict location optimization (favoring easily accessible items).

Currently, many warehouses employ two basic picking strategies:

1. Quantity-first strategy (full pallet priority): The system identifies and picks full pallets first, then handles partial pallets, aiming to complete bulk picking in fewer operations.
2. Reverse quantity strategy (partial pallet priority): The system prioritizes partial pallets to quickly clear scattered inventory and free up rack space.

However, when these strategies interact with drive-in rack layouts, problems emerge. For instance, a full pallet at the deepest rack position might be prioritized over an equally full but more accessible pallet at the second position, reducing overall efficiency.

To resolve these conflicts, we propose a strategy that simultaneously considers both item quantity and physical location. The core principle is to prioritize items that meet basic inventory requirements while favoring those that are physically easier to retrieve.

In drive-in racks, we must distinguish between:

• Logical position: The item's sequence within the rack aisle, typically related to movement order (LIFO/FIFO). In systems like SAP EWM, this might correspond to storage unit sequencing.
• Physical position: The item's actual accessibility. Positions closer to the aisle entrance are "shallower" and easier to pick, while deeper positions require more effort.

An ideal drive-in rack picking strategy should follow these principles:

• Primary principle: Meet core picking requirements (either full or partial pallet priority based on business needs).
• Secondary principle: Optimize physical accessibility by favoring shallower positions when primary requirements are met.

1. Quantity grouping: First, group items by quantity (full vs. partial pallets) based on business requirements.
2. Position sorting within quantity groups: For items in the same quantity group, sort by physical position using rack depth information from the warehouse layout.

Implementing this combined strategy in SAP EWM typically requires configuration of picking rules and potentially custom development.

SAP EWM's picking rules allow definition of priority and sorting logic through combination of fields. Custom sorting sequences can implement complex prioritization.

When standard configurations prove insufficient, SAP EWM's Business Add-In (BAdI) interfaces allow custom logic insertion during picking determination processes.

Beyond simple position sorting, we can implement a refined "pickability" score based on:

• Aisle depth
• Rack height level
• Operational space constraints

Beyond quantity and position, FIFO principles and expiration prevention require date management integration:

• Date field integration: Incorporating fields like Goods Receipt Date (GR Date) or production date into sorting sequences.
• Implementation approach: Configure sorting as: 1) Quantity grouping, 2) Date ascending (earliest first), 3) Physical position ascending (most accessible first).

1. Clearly define logical and physical position mappings for implementation teams.
2. Ensure accurate drive-in rack layout configuration in the system.
3. Maintain precise handling unit (HU) quantity and position data.
4. Conduct thorough testing before production implementation.
5. Coordinate picking strategies with putaway and inventory management approaches.

Optimizing drive-in rack picking requires balancing multiple dimensions through careful system configuration and potential customization. The ultimate goal is creating a system that responds efficiently to order requirements while maintaining inventory health and FIFO compliance.