Warehouse technologies: 3 trends to watch
| June 25, 2020
These days, many warehouses and distribution centers are under the gun to boost efficiency and productivity and ship products and materials faster than ever.
In the e-commerce industry alone, a recent survey by the global consulting firm Capgemini Research Foundation reported that 55% of consumers polled said they would choose a brand or retailer over its competitor if it offered a faster delivery service.
That said, a white paper titled “Warehouses of the Future,” published by the W.P. Carey School of Business at Arizona State University (ASU), says warehouses are becoming places “not just to store stuff,” but places integrated into supply chain processes. The paper goes on to say that, consequently, warehouses today are looking to technological advances to cut the cost of labor, boost productivity and speed up the flow of goods.
“In the future,” the authors write, “we see a trend to increasingly develop and implement technologies that address the need to improve both efficiency and cycle times inside distribution centers.”
Ryan Martin, principal analyst at the firm ABI Research says, “A lot of companies are turning to technology and automation, especially in areas where there’s the potential for human error. You want to be able to improve flexibility and agility and, just as important, to be resilient.”
The following are just some of the warehouse technologies to watch:
Autonomous Mobile Robots (AMR)
AMRs can perform many of the same tasks that driverless autonomous guided vehicles (AGV) are able to do, says Elliot Rabinovich, Ph.D., a professor of supply chain at the W.P. Carey School of Business at ASU and the white paper’s co-author. They can carry cartons, boxes and even pallets.
The big difference, however, is that while AGVs have fixed navigation systems, AMRs are equipped with intelligent navigation capabilities along with cameras and mapping systems so they can move autonomously around the warehouse and navigate around barriers without the need for reprogramming.
“AMRs have a greater degree of freedom to move around,” says Rabinovich. “They can adapt to a floor plan as opposed to the floor plan adapting to them.”
In the e-commerce arena, companies are using AMRs to reduce the amount of time pickers spend walking around the warehouse. AMRs can transport cartons to and from shelves so pickers can spend less time walking back and forth and more time focusing on their task, thereby improving accuracy.
“With automation, you can have robots deliver the products to the employees who can then assemble the orders, therefore eliminating a lot of the labor in picking the items,” Rabinovich says.
Automated warehouses and fulfillment centers of the future will need real-time connectivity and 5G technology can meet the challenge.
5G is the fifth generation of wireless technology, and it’s got the potential to make smart warehouses operate even more efficiently, Martin says.
That’s because 5G has greater bandwidth than 4G, which has been around for several years, meaning that it’s capable of carrying more data. In addition, 5G offers what’s known as low latency connectivity, so data moves faster between devices. With less lag time and greater bandwidth, 5G promises to make robotic technologies operate with more speed and reliability.
“In order to enable this real-time knowledge capture and insight, you need the right connectivity infrastructure,” says Martin, Existing Wi-Fi, he says, isn’t enough.
“Everything indicates 5G is going to be a key enabler of a lot of the capabilities real-time fulfillment is after.”
A form of artificial intelligence, machine learning involves the use of algorithms and huge datasets from which computer-operated devices can “learn” to perform tasks and make decisions based on past data without the need for reprogramming.
Rabinovich says the trend now is to combine machine learning with warehouse management systems. WMS software controls and manages warehouse functions such as tracking inventory, picking and shipping.
“Traditionally WMS has recorded what was coming into the warehouse, what was inside the warehouse and what was coming out,” he says. “But increasingly the trend has been moving toward machine learning to find new ways to adapt or preempt possible changes that may alter the state of goods coming in, those that are stored or those leaving the distribution center.”
“Basically, it’s about making the WMS more adaptable to what’s going on in real time,” says Rabinovich, “or to what may go on in the near future in the warehouse.”
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