Opinion:

In recycling facilities, people and machines work together. Machines handle repetitive tasks. People supervise the process and solve unexpected problems.

What if products could tell us when they should be recycled?

OPINION: Many products still contain valuable materials when they reach the end of their lives. Digital technologies and human expertise can help companies to know when products are returned and how they can be reused, repaired, or recycled.

Published

Every year, millions of products reach the end of their lives. Many of them still contain valuable materials. For example, electric vehicle batteries are complex, expensive, and full of valuable resources. But when a battery stops working in a car, it does not always have a clear path forward.

In my project, I study how digital technologies can help us manage these products better once they are returned. The goal is simple: make it easier to collect, transport, and recycle.

But there is a major challenge.

The problem: we don’t know where products are

Reverse logistics is the system that collects used products. It helps move them to repair, reuse, or recycling. This system is an important part of a circular economy.

But companies often do not know when products will return, where they are located, or what condition they are in.

This makes planning difficult. Imagine planning transport or recycling without knowing what will arrive tomorrow. Uncertainty like this makes reverse logistics expensive and inefficient.

But solving this problem is not only about technology. It is also about people.

A human-centric digital twin of the reverse logistics system

My research explores the use of a digital twin of the reverse logistics system. A digital twin is a digital copy of a real system. It uses product data, simulations, optimisation models, artificial intelligence, and robotic systems.

The system supports people who make decisions and carry out daily operations. Workers, planners, and operators stay in control. Digital tools give them better information and help them work more efficiently.

For example, better data about returned products can improve transport planning. It can reduce empty trips and make recycling easier to organise.

In recycling facilities, people and machines work together. Machines handle repetitive tasks. People supervise the process and solve unexpected problems.

Our research suggests that empowering human intelligence with digital technologies may be one of the keys to making this possible.

 

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