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E-waste Recycling June 11, 2024 03:30:01 PM

Lenovo Drives Down Electronic Waste with AI-Powered Device Refurbishment

Paul Ploumis
ScrapMonster Author
Leveraging AI to support device refurbishment for Lenovo MBG has already delivered significant efficiency improvements.

Lenovo Drives Down Electronic Waste with AI-Powered Device Refurbishment

SEATTLE (Scrap Monster):  A record 62 million tons of e-waste was produced in 2022. Of that amount, only 22.3% of the year’s e-waste was documented as having been properly collected and recycled.

Contributing to circular economies by repairing, re-using, and recycling old or broken devices helps reduce electronic waste and its impact on our world. At Lenovo, we have worked for years to ensure that our supply chains and manufacturing processes are as circular as possible. One of our recent initiatives includes offering refurbished devices through our recently launched Lenovo Certified Refurbished offering. And now we are tapping into the power of AI to help expand our refurbishment capabilities.

Traditional approaches to refurbishing devices are labor intensive, with engineers manually inspecting and testing each device to determine whether they can be fixed or harvested for spare parts. The refurbishment process also holds a wealth of information about the durability and common failure modes of device components—insights that can help inform future considerations around design and product lifecycle management.

“We recognized that AI holds tremendous potential to enhance the efficiency of our sustainable refurbishment initiatives,” comments Aaron Zhang, ISSC Reverse, Repair, Refurbish Director at Lenovo. “For engineers, it could help to automate time-consuming and repetitive device inspections and even recommend personalized refurbishment options for customers. And for Lenovo research and development teams, AI promises to deliver faster access to insights gleaned from the refurbishment process.”

To enhance our refurbishment services, Lenovo harnessed the power of Lenovo edge computing solutions, internet-of-things sensors, machine learning and computer vision technology to develop an AI solution that automatically detects device issues by analyzing images of internal components.

Built using AI algorithms optimized for quality control and predictive maintenance workflows, the Lenovo solution helps engineers identify faults, find the most effective repair procedures, and select the optimal replacement parts—all in real time. As part of a phased development process, Lenovo uses the solution to optimize and improve efficiency of inspection of used devices in Lenovo’s Mobile Business Group (MBG).

While still in its early stages, Lenovo’s AI-powered refurbishment initiative shows tremendous potential to enhance sustainability by helping more customers refurbish their devices. For example, in a recent study it was found that 70% of laptops discarded by first-time users can have double the lifetime by being re-used.

At Lenovo, 71% of devices collected by Lenovo are refurbished or re-used for parts, supporting a circular economy. Li comments: “Our customers not only increase the working life of their devices; they also typically enjoy enhanced specifications and a boost in performance as a result of the upgrades made by our engineers.”

Leveraging AI to support device refurbishment for Lenovo MBG has already delivered significant efficiency improvements. Since deploying the AI solution, Lenovo has increased the average output units per hour for a single model from 30 units an hour to more than 65 units—representing a 116% increase in efficiency.

Lenovo’s AI-driven refurbishment workflow has also delivered significant cost reductions. Zhang explains: “In just one year, we were able to reduce the annual costs associated with smartphone refurbishment by $100,000, while also ensuring that 100% of refurbished orders were fulfilled on time. In the coming months, we anticipate that we will be able to make a further saving of $110,000 by harnessing the AI solution to enhance production planning and optimize the purchasing of spare parts. These significant savings release more capital that we can reinvest in researching new design features to make our products even more circular and sustainable.”

By leveraging AI for refurbishment, Lenovo was able to gain:

116% efficiency boost in average hourly output units

$100,000 annual cost-saving

100% of refurbished orders fulfilled on-time

Courtesy: www.news.lenovo.com

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