What You Should Know about Goods-to-Person Fulfillment

What You Should Know about Goods-to-Person Fulfillment

The recent introduction of several goods-to-person order fulfillment systems calls for a thorough understanding of their potential fit into any logistics operation.

Most distribution centers use a person-to-goods picking model and operate on a manual paper-based system to compile orders. In such a traditional order fulfillment environment inventory is stored out on the floor and the most efficient pick paths are determined with the help of routing logic.

Distribution centers have used this mainstay person-to-goods order picking scenario for decades. But as the number of SKUs grows, fueled by market shifts such as e-commerce growth and the rising demand for just-in-time ordering, workforce consistency and availability have become less predictable. These factors have challenged the traditional person-to-goods fulfillment model.

It was once acceptable for a picker to spend 60 percent of the time traveling and 40 percent of the time picking. However, distribution executives are increasingly looking for more efficient solutions to minimize wasted time between picks and increase the number of orders processed per person. That’s why many of them are embracing a goods-to-person fulfillment approach using advanced technology for inventory storage and movement.

The Basics

The goods-to-person concept is simple: incoming goods are removed from pallets, either manually or automatically. The cartons and/or pieces are then placed into totes (smaller goods) or into trays (larger goods), and stored in high-density automated storage and retrieval systems (ASRS), carousels or robotic systems.

As orders are required to be fulfilled SKUs are automatically retrieved from storage and brought to the picker, either at a pick station where the operator picks into an order container or to an ergonomic palletizing station where items are placed on a pallet. Since the picker does not have to walk, the focus at the pick stations and pack stations is on ergonomics and high productivity.

Although some form of automated goods-to-person fulfillment options have been available for many years, it has just been within the past several years that an influx of extremely efficient goods-to-person systems have been introduced. This has been largely influenced by heightened processing capability and fully-integrated controls architecture developments, making these high-SKU-count, high-speed systems possible.

Goods-to-person solutions can incorporate high-density storage systems, pallet-based or tote/carton-based systems, horizontal and vertical carousels, robots and vertical lift modules.

Systems like Kiva, Dematic’s Multishuttle, TGW’s Commander, and Swisslog’s AutoStore and SmartCarrier are just a few examples of the more recent introductions that have evolved to facilitate rapid and accurate throughput of growing numbers of SKUs and smaller order quantities. These systems feature modular components and the flexibility to be scalable. They are especially suitable for high-rate capacity, changes in product demand profiles and the ability to accommodate load sequencing requirements.

Because goods-to-person systems present operators with only the goods needed for orders, when combined with pick-to-light or voice-activated technologies these systems cut down on the chances that workers will pick the wrong items, improving accuracy and productivity.

Selecting a Solution

A goods-to-person pick solution should be approached from a process perspective, not based on any specific automated technology. There is rarely a single solution that efficiently works across all of a DC’s SKUs.

A DC’s SKU and order activity must be closely monitored and analyzed to determine how that activity varies over time—even down to the level of variations on a wave by wave basis, if necessary. Factors evaluated may include daily unit volumes, units per order, lines per order, packing sequence, unit cube and cube movement, cartons per order, total SKUs and percent of SKUs in daily demand.

An operational assessment might include spikes in throughput, order cut-off times, number of fulfillment shifts, growth projections, initial capital investment, manageability, total labor, accuracy, product security, space and speed of processing required.

Such a detailed assessment may reveal the need for both an automated goods-to-person solution as well as a semi-automated or manual person-to-goods solution, operating in unison. For example, with a DC that is handling 5,000 SKUs, 90 or 95 percent of those SKUs may fit well into a highly automated goods-to-person solution. The remaining 5 or 10 percent, however, may be fast movers that will be on every few orders.

Those SKUs may be better suited for a more traditional pick methodology such as a carton or pallet flow rack if the order count is high enough. And those picks can be made in a relatively compact area, so pick walking is reduced while achieving volume throughput.

Rather than putting all SKUs into a goods-to-person automated solution, by separating out the fastest movers less capital would be spent for automation while still maintaining very high pick rates.

Medium and slow SKU movers are often a better candidate for goods-to-person automated systems. These are the SKUs for which the picker, in a traditional person-to-goods picking environment, will have to walk multiple aisles between picks. Eliminating this significant walk with a goods-to-person solution is where automated systems deliver their greatest pick and cost efficiencies.

Several other key points should be considered:

➤ A system’s susceptibility to single-point system failure. Systems like Kiva employ multiple, independently controlled robots, for example; if one section of the system was to be disabled for repairs the system would continue to operate at 100 percent functionality.

➤ The design flexibility to easily expand as DC volumes increase—particularly with the capability to independently scale throughput and inventory, both at the time of the initial investment and over the life of the system. Systems like AutoStore are adaptable and can be configured to fit different building heights, span multiple levels and even surround obstacles in the warehouse, such as pillars or walls. Additional storage space could be added by extending the system without interfering significantly with ongoing warehouse operations.

➤ The ability to store and retrieve orders simultaneously, as opposed to sequentially. This capability, such as can be found in the Multishuttle, can accommodate high throughput.

➤ The ability to integrate external, manual pick stations into an automated system’s shuttle systems, such as for handling single items and small cases. This can add flexibility for distribution centers.

➤ Energy efficiency, not only consuming less power while maintaining excellent weight-to-payload ratios, but also using energy recuperation modules to generate and store electricity from system shuttles while in operation. These systems can operate as lights-out solutions and without the need for air conditioning, further reducing energy usage.

No one system embodies all of these attributes, so logistics executives should assess which characteristics are critical to their requirements and identify a system that best meets them.

Conclusion

A properly applied goods-to-person system can double or triple picking activity. Although the biggest challenge to justification is the initial capital investment, the long-term benefits can outweigh that.

But before moving forward with any project, a DC’s executive team should determine their needs by conducting a thorough, unbiased review of system options.

Jeffrey Graves is president of Sedlak Management Consultants (www.jasedlak.com), a supply chain consulting firm with expertise in the retail, manufacturing, wholesale, direct-to-consumer and third-party logistics industries.

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