How Zebra Technologies Uses Machine Vision to Transform Production Automation

Machine vision is the focus of Machine Design’s Takeover Topic Event (Aug. 12-16, 2024). Covering the gamut of vision systems, the lineup includes case histories, trends and interviews with notable players to watch in this space.

In the accompanying video, Andrew Zosel, senior vice president and general manager, Zebra Technologies, explains the vision and strategy behind recent acquisitions and the resultant solutions. Machine vision is a significant part of that investment and future growth at Zebra, said Zosel.

(In parts 2 and 3 of this interview series focusing on machine vision, Zosel elaborates on the following questions: Given the advancements in technology, are we still delineating between machine vision and computer vision? How are the economics of machine vision changing? What is driving the ubiquity of machine vision?)

Research commissioned by Zebra revealed that 70% of survey respondents plan to implement computer vision within the next five years. Published in June 2024, the 2024 Manufacturing Vision Study found that 86% of manufacturing leaders noted they were struggling to keep pace with technological innovation and to securely integrate devices, sensors and technologies across their facilities and supply chains. Survey respondents comprised 1,200 C-suite executives, as well as IT and OT decision-makers across various manufacturing sectors.

During a stopover at Zebra Technologies’ booth at Automate 2024, Machine Design learned from Zosel just how much Zebra is leaning into building solutions that address such vulnerabilities. The variation and number of technology applications displayed revealed the pace at which Zebra has been filling in its automation ecosystem in its effort to evolve into a full-solution enterprise that can orchestrate what manufacturers on their own cannot.

Expanding Zebra Technologies: Growth in Scope and Scale

Those familiar with Zebra Technologies likely will associate the company with its industrial printing capabilities, including scanning, track-and-trace and mobile computing and software solutions. “Our industrial are industrial printers used throughout the world,” said Andrew Zosel, senior vice president and general manager, Zebra Technologies. “The majority of the labels that go on boxes around the world, identifying and giving items a digital voice, are printed using Zebra printers because they’re extremely reliable and rugged. And that’s where the original Zebra brand came from.”

In 2014, a $3.45 billion acquisition of Motorola Solutions’ Enterprise business, which included handheld scanners and mobile computers, transformed both the scope and scale of Zebra’s portfolio, then expanding further into asset visibility, traceability, barcode scanning and barcode printing capabilities.

Another transformative year was 2021. Zebra acquired Fetch Robotics, Adaptive Vision and Antuit AI that year, effectively launching their machine vision and fixed industrial scanning portfolios. The acquisition of Matrox Imaging, a manufacturer of frame grabbers, vision controllers and imaging software, followed in 2022.

“We’ve invested significantly, both organically with our own internal developments coming from our existing teams, in new cameras and vision and machine vision, fixed industrial scanning products, but also made a couple of significant acquisitions over the past few years in the vision space, including, Adaptive Vision out of Europe, as well as company called Matrox out of Canada.”

Combining Hardware and Software for Machine Vision Solutions

Despite having a relatively new position in the machine and computer vision market, bringing together advancements in robotics, machine vision, automation and digital decision-making has been a surefire way to boost stealth and agility at once.

“Through these acquisitions, the biggest and most important part is still the software and the algorithms and its capabilities,” said Zosel. “That’s what we’ve focused on developing and acquiring, especially the traditional machine vision capabilities such as the deterministic algorithms or however you want to call them. And a lot of development in AI and, specifically, deep learning.”

Zosel pointed out that there are multiple ways to make vision systems work. The simplest method could be to use a vision sensor or a smart camera, which might comprise an all-in-one, fully integrated lens, light and computer in one product.

“We offer those types of products, all the way to completely disaggregated-type systems, where multiple parts come together, such as a frame grabber board in a high-end PC with a separate set of high-end cameras with separate lighting,” Zosel said. “It’s the same basic architecture of lighting, lensing, processing and compute. But it depends on the integration as well as the performance requirements of the application.”

From Zebra’s perspective, said Zosel, the intent is to offer all the above. “Zosel’s platform advantage is that it has that scalability to offer everything from basic, simplified, lug-and-play-type product, all the way up to very complex, high-end systems doing either extremely high resolution or extremely high-speed processing, or both,” he said.

Long-Term Strategies: Automation and Augmentation in Manufacturing

Fundamentally, Zebra wants to help our customers find ways to meet the challenges they encounter, said Zosel.

Packaging sustainability is a case in point. Some of Zebra’s customers are moving away from plastics by opting for thinner plastics and paper-based packaging. Zebra is helping them with inspections and helping customers along their sustainability evolution by providing products and platforms that are scalable. explained Zosel. For instance, a customer may start with 2D machine vision, but “plans for scalability to 3D and for using more advanced AI. A lot of our systems and efforts are around creating that scalability and providing that path for our customers,” Zosel explained.

Zebra’s study found that over the next five years, manufacturing leaders plan to implement various automation technologies, including robotics (65%), machine vision (66%), radio frequency identification (RFID) (66%), and fixed industrial scanners (57%). The study highlighted that the adoption of these automation solutions is driven by several factors: the need to assign high-value tasks to the workforce (70%), achieve service level agreements (69%), and increase flexibility on the plant floor (64%).

Zosel said that Zebra is looking at ways to make products “easier to deploy, easier to integrate with robotics, easier to automate and integrate with material handling systems, as well as coming up with clever ways that deep learning and AI and different imaging technologies can be used to help in customers’ applications.

Watch additional parts of this interview series with Andrew Zosel:

Part 2: Deep Learning Algorithms Help Vision Inspection Systems See Better

Part 3: How Deep Learning Complements Machine Vision Solutions