Member Since 1984


AIA - Advancing Vision + Imaging has transformed into the Association for Advancing Automation, the leading global automation trade association of the vision + imaging, robotics, motion control, and industrial AI industries.

Content Filed Under:


Bar Code/OCR Reading Bar Code/OCR Reading

Vision Technologies Boost Warehouse Efficiency, Transparency

POSTED 04/17/2017

 | By: Winn Hardin, Contributing Editor

Amazon has gotten warehouse efficiency down to a science, and vision and imaging technologies share in the credit. The SICK Inspector P30 2D camera, used for positioning in merchandise retrieval, delivers 15% extra picking cycles per hour. Meanwhile, human pickers are equipped with handheld image-based barcode readers, and merchandise gets scanned at a series of points throughout the fulfillment process.

It’s not just retail giants, however. Warehouses of all types and sizes are realizing they don’t have to be an e-commerce gorilla to benefit from vision and imaging offerings ranging from 3D empty tray detection to smartphone-based scanners. Not only is the vision industry providing the hardware, but they’re helping their warehouse customers leverage the data generated by cameras, sensors and imagers across the entire enterprise in order to maximize efficiency and productivity.

Moving Beyond the Barcode
Barcode readers continue to be the bread and butter of imaging applications in the warehouse. These industrial imagers may require less complexity than their traditional machine vision system counterparts, but they nevertheless have a demanding job.

“Compared to factory automation and its many applications, the warehouse is more focused and contained because you are just trying to read a barcode and guide a box where to go,” says Bryan Boatner, Director of Product Marketing - Mobile & Hand Held Products, ID Products for Cognex (Natick, Massachusetts). “But in another sense, because the boxes are moving so fast and throughput is at such a premium, it can be a lot more challenging.”

When image-based industrial barcode readers first debuted, their primary value proposition was providing better read rates and capturing more data than their laser scanner counterparts ever could. In reading direct part mark (DPM), 1D, and 2D barcodes, image-based devices allowed warehouses to save images of codes that didn’t read in order to perform troubleshooting and root cause analysis to help improve the process.

Once customers saw that benefit, they started to explore ways to utilize other information available from the barcode image. Until recently, much of that data was tossed aside, says Bradley Weber, Manufacturing Industry Product Specialist and Application Engineering Manager at Datalogic (Minneapolis, Minnesota).

“It used to be taking that image, running it through algorithms such as reading the barcode, and processing it right then and there, and then moving onto the next package,” Weber says. “It’s changing now where a lot of that information is being stored and analyzed for later so you can identify trends over time.”

To help keep its customers’ data from languishing, Cognex developed the Cognex Explorer Real Time Monitoring (RTM) system. When the Cognex DataMan detects an unread barcode, it automatically transfers the image to RTM. Using the company’s vision technology, RTM evaluates each image and categorizes them into groups based on their error — for example, missing labels, poorly printed labels, and so on. Categorized images are stored in a database accessible via web browser.

Just as warehouses are relying on the additional data generated by barcode readers, they’re embracing a multipart vision system to track a product from the front end to the back end. “Datalogic is helping our customers to build a fingerprint of the package traveling through the facility using different vision technologies, including barcode readers that integrate OCR [optical character recognition] functionality, sensors that detect the presence or absence of a package, dimensioners that scan the package to provide its volume, and machine vision cameras capturing what is on that package,” Weber says.

For its part, Cognex is investigating ways to employ its vision technology on its handheld readers and mobile terminals to automate OCR. “We plan to demonstrate to customers how they can use vision on handheld readers to read ZIP Codes off the label in addition to scanning the bin location barcode,” Boatner says. “You can even conceive the ability to do the entire form reading where you convert printed fields to an automated data collection service.”

Image-based warehouse management machine vision systems are enabling companies to be more transparent — and therefore better partners — to their customers. Datalogic’s Weber says that all information gathered together from dimensioner, weight, images, or other sensors can be combined to have a unique ID for a package. “The customers will be able to access it all,” Weber says.

Shop Floor to Top Floor
Delving this deep into the data, of course, depends on the ability of the manufacturing plant or distribution center to connect disparate business activities, enabling dataflow for centralized decision-making. But many of these systems, including warehouse management, continue to operate in silos.

To tie warehouse activities into front office operations — colloquially known as “shop floor to top floor” — vision products and systems ideally will integrate with an enterprise resource planning (ERP) system, which centrally manages an organization’s business activities and the data generated by them.

But an ERP comes with its own challenges. “The ERP does just enough to get by, and it’s not very nimble,” says Dan Hare, vice president of Matrix SSI (East Sanborn, New York), which provides technology solutions to centralize inventory control. “It doesn’t do a good job at device management, which is part of the inventory control because you’re printing labels and scanning. We understand the workflow that happens in the warehouse better.”

Of particular focus for manufacturers is automatically tracking work-in-process inventory, or the raw materials that are transforming to finished goods. “A lot of this is being done with serialization and lot-type tracking, and older systems just don’t do a good job of that,” Hare says. “We’ve seen a big uptick in our solution used as an overlay for [ERP systems such as] SAP and Oracle, and that’s even in brand-new installations.”

And without being responsive to the needs of the warehouse worker, workflow is likely to suffer. “Many ERPs are designed for big computer screens with a mouse at a desk,” Hare says. “Matrix SSI is designed to run on handhelds on the shop floor.”

Matrix SSI, which is hardware agnostic, has spent the past 15 years building an integration tool to connect all silos and disparate systems in a warehouse. It’s an engineering effort that vision companies are starting to make for their customers as well. Cognex’s RTM, for example, harnesses all the data it collects on images, which can be distilled and presented to office managers so they can assess the information and make changes.

Meanwhile, Cognex’s MX-1000 vision-enabled mobile terminal employs technology used across the entire enterprise. The MX-1000 leverages a variety of Android and iOS smart phones as the user interface of the device. The phones are set within a ruggedized housing equipped with Cognex barcode reading algorithms. “If you have people in the front office running apps on their Samsung Galaxy S7 or iPhone 7 to automate workflows, you can use that same device in our MX-1000,” Boatner says. “It’s a much easier solution to deploy because you have one device that is managed by IT that is deployed in your warehouse, front office, field team, and so on.”

Today, the machine vision industry is chasing every opportunity to catch the “killer app,” which is usually associated with the massive installed base of smartphones around the world. The warehouse — with its controlled, demanding environment — may be the gateway that brings machine vision technology to everyone’s pocket, whether they are a distribution center manager or a new customer.