The future of device processing lies in the powerful partnership between humans and robotics. While human expertise brings insight and adaptability, robotics deliver the precision, consistency, and scale needed to ensure device quality and build consumer trust. Together, they enable accurate, verifiable data through innovations like the Device Passport™, transforming how the secondary device market operates and grows.
In my view, future growth comes down to first principles. Everything hinges on one deceivingly simple question. Do the devices on the market meet consumer expectations regarding quality? The answer must be yes. And increasingly, that answer must be verifiable, backed by a trusted, transparent record of the device’s condition and history. This is where the concept of a Device Passport™ becomes essential.
The reality is that it is often challenging for companies that assess, refurbish, and resell pre-owned devices to answer yes to this question. Operating in the highly nuanced secondary device market is difficult.
This is especially true for device processing. The smartphone revolution didn’t actually make phones smart—it made them infinitely more complex. This complexity extends to manual device processing that assesses devices across cosmetic, functional, and structural categories. The work is exhausting and repetitive. It’s also high stakes because it impacts revenue generation and consumer trust.
As important as device processing is, human subjectivity is a limiting factor. With humans conducting cosmetic grading and functional testing, variability is unavoidable. Not every tester will make the same decisions. Even the same person can evaluate the same device differently at different times. Our analysis shows that human testers incorrectly grade devices half of the time. That’s through no fault of their own—it's simply due to being human.
Humans are doing their best at the challenging work of device processing. But is manual testing the best use of humans’ time and unique skills?
Given our work at Apkudo, my answer to this question is no surprise—device processing is an exercise in addressing complexity. It demands consistency, accuracy, and scalable repeatability, which humans alone cannot deliver. This is why robotics for device processing are so transformative. They remove human subjectivity to improve accuracy and predictability, and add speed to operations and revenue recognition.
Introducing robotics to device processing has been a journey. The truth is that solving problems with robotics and advanced automation is fundamentally hard. The more niche or specialized the task, the harder it is. When we first started, it took us three years to get a robot to guide a USB-C connector into a USB port with the appropriate level of precision and robustness to operate at scale.
Today, using display functional assessment as an example, our robotics perform pixel-by-pixel analysis to detect issues like discoloration, convexity defects, pixelation, and burn-in. Many of these flaws aren't even visible to the human eye. This level of granular, objective data is precisely what’s needed to build a comprehensive and trustworthy Device Passport for every single device.
I fully recognize that some in this industry have hesitations or ambivalence about robotics' evolution. They worry that accuracy and efficiency gains from robotics come with consequences for humans. It’s no wonder—tension between technological progress and human well-being has been a central theme in every industrial revolution since the late 18th century.
However, this evolution isn’t an either-or proposition for humans and machines. When robotics take over repetitive tasks, we can realign humans to higher-value ones. This powerful partnership is instrumental to building consumer trust in the secondary device market. Robotics isn’t a story about humans or machines. It’s about humans and machines.
Consider the automotive industry, which is now the top adopter of industrial robotics in the United States. Basic robotic arms and automated conveyors appeared on auto assembly lines in the 1960s. By the 1980s, automation technology, sensors, and computer-controlled systems had robots handling more sophisticated manufacturing tasks. Flash forward to today, and AI-powered robotics on automotive assembly lines are doing everything from inspecting parts and detecting defects to working with humans on adaptive welding, customization, and intricate component placement.
This decades-long evolution has created new roles for human auto workers in the robotics systems’ maintenance, programming, quality control, and troubleshooting. We’re seeing a similar progression in our industry. Humans are informing grading algorithms, monitoring robotics, and focusing on device exceptions. With robotics extracting thousands of data points from devices to reveal their true state, we have knowledge beyond a grade or a pass-fail.
It’s humans who can translate this tremendous insight, now captured and made actionable as a single source of truth in the Device Passport, into new business value. I believe there’s nothing more exciting in this space right now.
I’m encouraged by this industry’s focus on scaling with robotics and what it means for growth and the circular economy. The more devices are manufactured to be practically sustainable and processed without requiring a decade of robotics development to untangle complexity, the better.
At the same time, we can’t forget the human side of the robotics evolution. Apples-to-oranges comparisons of human and robotics testing are not helpful. We already know the answer because we know humans have limitations. It’s much more productive to combine cutting-edge robotics and uniquely human skills to take device processing—and the future of this industry—to a new level.
Interested in taking device processing to a new level? Learn how to navigate the challenges and opportunities of bringing humans and robotics together for functional testing and cosmetic grading.
