Header Title
Rethinking recycling – with robotics
Rethinking the economics of recycling
US company AMP Robotics claims to be rethinking the economics of recycling by using robotics and AI to sort waste streams with exceptional speed and accuracy, in order to meet the needs of today’s material recovery facilities and recycling operations.
The company profiles itself on breakthrough technology that automates the identification, sorting and processing of complex waste streams, making it possible for a wide range of material recovery facilities to boost efficiency and extract maximum value. This would seem to result in a strong commercial rethink of recycling operations and what they can achieve.
Dirty end of manufacturing processes
AMP Robotics in the US currently provides a triumvirate of products focused on the requirements of recycling operations – which is an interesting business model in the field of robotics, where the vast majority of products seem to focus on the manufacturing end of the product cycle.
By bringing the strengths of robotics and AI to the “un-sexy” opposite end of the overall cycle, AMP Robotics may well be carving out a less-crowded niche for themselves – and doing so in a major growth industry that simply isn’t going to go away. They may even be saving the ethical bacon for robotics – which is inherently vulnerable to criticisms of being part of the problem of continually flooding the world with more “stuff”.
Powered by artificial intelligence
AMP Neuron™ serves as the “brain” for the company’s Cortex™ hardware, using machine learning and industrial artificial intelligence (AI). By processing large amounts of data and identifying patterns in this data, AI makes it possible for robots to continuously learn from experience, and adjust to the characteristics of new materials and new input flows for sorting. The Cortex robots then become “intelligent” so they are able to carry out specific high-speed sorting and picking tasks, so the selected and sorted materials can be placed into appropriate collection bins for resale processing.
Turning data into decisions
Material for recycling is usually in the ultimate analogue format – physical, messy, mixed and unpredictable. The third leg of the AMP Robotics business model therefore lies in the transformation of all this grungy nastiness into actionable data with the potential to add commercial value.
AMP Insights™ is an online data visualisation tool that monitors and digitises material streams, measures sorting and picking performance, provides transparency about material composition and productivity, and helps companies towards data-driven operational decisions. The data transparency made possible by AI (apparently) also boosts productivity via a combination of operational insights and advanced analytics.
changing the economics of recycling and making it more sustainable
Greater value from any given waste
According to the company’s own material, AMP Robotics focuses on material recovery facilities and recycling businesses that process construction and demolition debris, e-waste and vehicle scrap. All these are widely recognised as relatively high-value waste, making the commercial attractions are pretty clear.
But AMP Cortex also makes it possible to deal with a broad spectrum of municipal solid waste including newspaper, plastics, cartons, cardboard, cups, aluminium and polyethylene. According to the company’s claims, materials can also be accurately identified right down to the stock keeping unit (SKU) and brand, which provides data transparency and categorisation with unprecedented levels of data granularity. This is vital at the low-value end of the waste spectrum, where inaccurate waste mixing is prevalent and cost/value margins are tight.
This robotics-driven approach seems to have the potential to overcome the limitations of many manual sorting processes, the market pressures for high purity levels to ensure the value of recovered waste, and providing a way to extract the greatest commercial and environmental value from a broad spectrum of waste streams. Supporting an industry with perhaps the biggest growth potential of all seems an attractive business model – not least when the capabilities can almost certainly be applied elsewhere …