Identifying the characteristics most needed for an effective picking solution may seem obvious. High visibility, robust order-pick displays and flexible mounting methods allow a system to easily adapt (increase or decrease) with warehousing operation requirements. Simple intuitive software must be part of the mix when selecting best-practice picking solutions.
Trevor Blumenau, the CEO of Voodoo Robotics, based in Plano, Texas, argues that Industrial Internet of Things (IIoT) real-time, Web-connected, leased pick-to-light devices are the best choice for more than 90 percent of the distribution, warehouse and cellular manufacturing assembly market. With such a declarative claim, it seems imperative to dig a little deeper and find out whether that assertion holds water.
Blumenau readily admits that a one-size-fits-all picking solution does not work, and that achieving the highest productivity from a warehouse operation may require different technologies, which may be better-suited depending on the order frequency and value of a particular stock-keeping unit (SKU).
Comparing pick technologies side by side often reveals that pick-to-light solutions have a clear edge over other solutions when picking accuracy is measured. The light indicators make it difficult to pick from the wrong location—or the incorrect amount—when the light is both the pick instruction and location indicator.
There is also a clear cost advantage and scalability to pick-to-light solutions determined by the number of SKUs, as a display is required for each SKU picked. With voice or RF scanning equipment, the variable cost is determined by the number of operators picking.
These characteristics for picking solutions are a great starting point for finding a cost-effective and efficient solution. But don’t measure against the real value: picking the right product at the right place at the right time.
Furthermore, when purchased in the old-fashioned way, pick lights represent a large capital equipment purchase with fixed costs, immobile equipment—a serious detriment with fluctuating inventory—and variable SKUs.
SKU Proliferation Demands Cost-Effective Picking Solutions
With exponential growth in SKUs, the permutations of a given product can be complex. That variety and variability does not need to translate into the design, deployment and maintenance of an effective picking solution. Blumenau insists that hardware components should be modular and user-replaceable, minimizing maintenance and support costs.
While assembly-line processes can be complex, particularly in food logistics, e-commerce, business-to-consumer organizations, spare parts assemblies and a wide variety of consumer goods distribution centers, all are achieving greater throughput with pick-to-light solutions.
Pick-to-Light and the IIoT
The real test of the claims about pick-to-light were validated when looking at the technology in a service model. When the devices are Web-connected, providing real-time accurate picking data, immediate corrective actions can be made on the plant floor.
Analysis of most warehouse orders will show a Pareto curve, in which a small number of the SKUs being processed account for a large percentage of the orders. These fast-moving items are the “A” parts. Any small amount of efficiency gains in picking these “A” parts will have a relatively large impact on the overall productivity of the entire operation.
Having these devices leverages data with authentic IIoT technology. The old model of only allowing a picker to know if he or she picked the correct product at the workstation is not a system-wide real-time visibility that benefits the entire operation.
These devices can even instruct quarantining information or out-of-stock data. The messaging can be directed to a picker, by name, and in the language spoken. It’s a game-changing disruptive approach to pick-to-light technology.
IIoT Picking Allows for the Elimination of Costly Mispicks
Avoiding mispicks is critical when outsourcing order fulfillment, according to Blumenau. Since businesses large and small are outsourcing order-fulfillment requirements to third-party logistics firms, the ability to utilize IIoT data ensures that manufacturers can keep tabs on operational costs. Nothing represents a negative impact on relationships with customers more than product mispicks.
Just one incorrectly shipped SKU in the e-commerce space can be the entire margin of a shipment. Often, the corrective action involves reshipment using costly overnight delivery services like FedEx to keep customers happy. With IIoT oversight in real time, such mispicks can be completely avoided.
Voodoo Robotics’ starter kit allows customers to test the efficacy of Blumenau’s solution, including access to inventory management known as SKU Keeper. It is vendor-agnostic and works with most warehouse-control systems and warehouse-management systems. The ability to utilize these IIoT sensors increases effective inventory management, cycle time counting and the ability to conduct single picks or batch picking. Without the expense of costly RF guns, operations or warehouse managers (onsite or off) can verify items picked and then pack them into boxes.
Validated Claim: IIoT Pick-to-Light With Upward and Downward Scalability
Call it the icing on the cake, but Blumenau’s bold assertion really hits home in the firm’s go-to-market strategy. For the first time, users do not buy lights—they lease them, just as software moved to the software-as-a-service (SaaS) model years ago. Lights are leased monthly. If more are needed, more are ordered. If fewer are needed, they are returned. This pay-as-you-go approach changes the entire consideration about testing the concept’s efficacy.
There is no capital equipment purchased; users get started for $500 and test the product within their own environment. This scalability up or down is particularly crucial in warehouses experiencing any time of seasonality or variable expansion/contraction.
Thomas R. Cutler is the president and CEO of Fort Lauderdale, Fla.-based TR Cutler. Cutler is the founder of the Manufacturing Media Consortium, which includes more than 6,000 journalists, editors and economists writing about trends in manufacturing, industry, material handling and process improvement. He authors more than 500 feature articles annually regarding the manufacturing sector. Cutler can be contacted at [email protected] and followed on Twitter @ThomasRCutler.