Optimizing Batch Picking with Software


Processing maximizes order fulfillment efficiency

Batch processing has proven to be a highly effective order fulfillment method for retailers, wholesalers, and business-to-business distributors. There are two types of batch processing: wave and waveless. Wave order processing is effective and widely embraced by order fulfilment operations worldwide. However, order fulfillment operations that have transitioned from wave batch processing to waveless batch processing have experienced increases in throughput capacity of up to 40% with labor productivity increases of up to 20%. This page provides a description and comparison of wave and waveless batch picking.

Batch picking in waves

Order fulfillment operations were originally designed for workers to process one order at a time. As the order fulfillment process evolved, warehouse managers determined that order assembly could be made more efficient by picking multiple orders with one pass through the warehouse. 

This process assigns a group of orders to a batch. It became known as batch picking. As order volume increased, order management software was developed to batch pick and process orders strategically in waves.

However, wave batch processing has some inefficiencies. Each batch of orders to be picked (known as a wave) must be completed before a new wave batch is started. And that batch cannot finish until all the orders are picked and until there is a position/destination for each of those orders to be placed. 

The number of available destinations needs to equal the number of orders. Even if a fast worker has completed all picks assigned, this worker cannot start the next wave batch. This means workers become idle, as there is no available position/destination to send the picked items. To increase productivity for wave-based processing, a buffer is included to temporarily hold picked items until a destination is available. 

Wave batch issues

Wave Transitions: A wave transition occurs when workers complete a wave batch. During wave transitions, the productivity drops significantly as warehouse staff is idle waiting for work.

Wave Tails: Even before a wave finishes, during the wave tail, productivity drops as a result of diminishing wave batch size.

Exception Handling: Exceptions, such as shorts and picking errors, delay the completion of a wave. These anomalies diminish productivity until resolved. Problem resolution teams need to fix exceptions prior to the start of the next wave.

Priority Orders: Urgent or special handling orders cannot be introduced or activated immediately. These orders need to wait for the current wave to complete. When multiple waves are planned, all waves must be complete before processing priority orders. And the planned waves must be re- planned again with the priority orders.

Waveless batch picking

Waveless batch picking is a single-batch processing order fulfillment method that increases productivity and operational effectiveness by synchronizing workflows in real time. It uses a dynamic strategy that is based on a revolving queue of orders. Waveless picking “pulls” work to resources and processes orders on-demand, continuously and dynamically instead of in static waves and is a highly effective method of managing order fulfillment.

Every time an order completes, a new order is activated for processing. Waveless picking evaluates each order immediately upon receipt and calculates urgency level for real-time prioritization, planning, and execution. It adds the next best order to execute based on priority and resource availability. The queue is always revolving and re-prioritizing.

This approach includes real-time decision making — the processing plan is not pre-defined and rigid, but rather determined based on current conditions. Since the warehouse staff and order destination status is available in real time, the execution software can direct the order fulfillment process with an “on-demand” strategy.

For example, with wave-based picking applications, as soon as one task is completed, workers are assigned the next task based on their current location and the inventory in the pick module. In waveless picking applications, automated inventory storage fully uses the capacity of a buffer to maintain an even and steady workflow in and out of storage. 

Benefits of waveless batch picking

  • Up to 40% increase in throughput capacity

  • Up to 20% increase in labor productivity

  • Reduces order cycle time

  • Priority orders processed without delay 

  • Provides constant, real-time insight to work-in-progress status

  • Removes peaks and valleys in activity, the entire operation remains balanced

  • Eliminates wave transitions with a revolving dynamic batch

  • Picking errors, shorts, or exceptions affect only one order, not the whole wave 

  • Operational effectiveness for proposed applications can be verified with simulation modeling

  • Reduces initial capital investment with less automation hardware (wave buffers not required)

  • Reduces cost per order

  • Requires less warehouse space

  • Retrofits into existing wave batch operations 

  • Supports omnichannel strategies

Dematic software for waveless batch picking

Dematic software for waveless batch solutions releases work based on order priority, order age, shipping request, worker status, available resources, and available inventory.

It anticipates when and where resources will become available. Resources of a distribution center include inventory, labor, and material handling automation such as storage sub-system, conveyor, goods-to-person workstations, pick modules, put walls, circular unit sorters, and packing workstations.

Dematic software uses an “in-transit queue” to manage the work release process. The systems do not limit the size of the batch to the number of physical destinations. With dynamic/revolving order batch, the work-in-process or in-transit queue is larger than the total number of destinations. It accounts for activated orders that are still in transit to the destinations and synchronizes the timing of resource availability.

Dematic software anticipates the number of resources needed and then releases the optimum number of orders. By the time the order arrives at the destination, a space will be available. For example, in a store replenishment application with 1,000 order positions in put walls, there can be 1,400 active orders in the in-transit queue of the dynamic/revolving order batch. 

Resource Optimization algorithms in Dematic software allow each section of a facility to maximize the number of orders processed while ensuring that downstream resources will have available capacity to handle arriving work.

Resource Optimization algorithms allow the different areas of the facility to operate more efficiently. Each area can increase throughput without risking diminished performance. Orders don’t get delayed in the transition points between areas. Managing all the areas of the facility with resource optimization algorithms keeps all areas in synchronization. Each operational area can be managed and optimized more effectively as a de-coupled unit.

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