Revamping End-of-Life Technology Processes with Intelligent Automation

September 15, 2022 | 4 min read

Adam Montoya, VP of Industry Solutions, Bright Machines

Manufacturing is about creating new products and bringing them to market as efficiently as possible. It’s time, however, for manufacturers to be more thoughtful about end-of-life processes as well, as they can have a detrimental impact on the environment and our businesses if mishandled or mismanaged.

A Global E-waste Monitor report found that a record 53.6 million metric tons of electronic waste (e-waste) was generated worldwide in 2019, which is expected to double by 2050. Worse yet, less than 20% of used electronics are recycled and, instead, are often exported to developing countries and thrown into landfills. 

Exporting or ignoring the problem is no longer an option. Manufacturing pioneers need to rethink, rework, and start to reuse the components that still have something to give–to truly consider the entire product lifecycle. At Bright Machines, we understand that pinpointing what those pieces are and retrieving them with efficiency is of utmost importance, which is why we’ve built intelligent automation technology to help.  

How It Works Today  

When a server nears its end of life, it’s either destroyed to ensure that sensitive data is destroyed with it, or it’s dismantled and storage devices wiped so that parts can be reused and sold for less demanding systems. It can also be “recycled” down to its precious metal parts in Southeast Asia, which incurs costs and emissions from shipping, and once there, the parts end up in a landfill or are recycled by people working under exploitative labor practices.

At end-of-life, some parts of a server are still useful, but getting to them is complex. For example, a company might hypothetically know what’s inside a server according to its original configuration, but in actuality, every server is a little bit different—pieces such as memory or processors could have changed during its first lifespan. The final make-up of a server, then, can be quite different from its original configuration, which means the disassembly process will be unique to each server as well.

Manufacturers need to have the ability to navigate what can feel like a “random” configuration—a complex, laborious, and error-prone task, which is why there’s an entire market centered around harvesting servers and reusing components. This market focuses primarily on two business cases: a company will gather old servers, ensure there are still usable parts, then sell them to global technology companies that need service spares on hand. Or, a company could specialize in securely destroying the servers in order to ensure sensitive customer data does not get into anyone else’s hands. 

Leveraging Intelligent Automation Within the Entire Product Lifecycle

Giving life back to the technology that still has value is good for the environment and for business. However, improving the end-of-life process will require both a different way of thinking and intelligent technology with machine vision to know the difference between what the specs say versus what is actually in the server.

Say a server has 16 memory slots, but only half were populated with dual in-line memory modules (DIMMS). One engineer might evenly space the DIMMS so there’s one slot filled and then one slot empty to maximize the thermal efficiency, while another engineer might add in the eight DIMMS on one side for simplicity. A traditional automation solution might be unable to understand the server’s configuration and detect where the memory DIMMS are located, which would likely require manual processing of the unit.

On the other hand, an intelligent automation solution with machine vision, perception, and artificial intelligence capabilities like our Bright Machines Microfactories can read the machine, interpret what’s in it and where everything is located, then compare it against the blueprint version so the engineer can work through a path forward. Our Microfactory technology, which leverages decades of deep software and manufacturing process expertise, can then intelligently sort, separate, and remove components and annotate any specific variances that the customer would need to know.

The potential benefits are numerous:

• Components with sensitive data can have machine-driven proof of destruction
• Systems with usable parts can be rapidly triaged, harvested, and re-purposed
• Carbon footprint can be reduced by minimizing or eliminating the need for hardware products being shipped to other countries
• Economic incentives could be associated with responsible handling of these assets

Revamping how companies go about the end-of-life process with intelligent technology can provide a pathway to immediate and long-term sustainability practices and additional revenue streams. It’s a no-brainer.

To learn more about our capabilities in building the backbone of AI, visit Bright Machines.