Website Cookies

We use cookies to make your experience better. Learn more on how here

Accept

Modelling of a modern MRF

Paloma’s paper has a dual focus on two of the challenges faced by MRFs today:

  1. The challenges associated with efficiency, waste composition variation and waste sampling methods.
  2. Optimisation of plant functions, given operations, legislative and stakeholder pressures and the economy.

Through exploration of these challenges, the research interrogates as to whether improvements in mechanical sorting processes will affect the impact on recycling rates, including purity, recovery, cost and profitability?

It asks this question in the context of innovative intelligent technologies and the emergence of their role in future-proofing MRFs.

recycleye

Paloma concludes by asserting the vision for the modern MRF: a wholly connected facility, operating as one integrated system in which the machines communicate with one another in order to adapt to the materials approaching them.

Therefore, Machine C would adapt the variables of its features based on the information it receives from Machine A and Machine B about the conditions of incoming material, in order to be optimised accordingly.

Overall, to maximise efficiency from an end-to-end sorting process, the efficiency and intelligence of each sorting technology must be lent to his peers, in order to create a collective, harmonious orchestra. Only by equipping subsequent machines to anticipate material features learnt by his predecessors earlier in the process, can a modern MRF deem their sorting process entirely efficient.

WasteNet

Single Shot 2D Image to 3D Model

This research consists of 2 papers offering differing reconstruction approaches to obtain high accuracy inferences of 3D structures with textures from 2D single shot images….

READ POST
WasteNet

Decentralised and Digitised Mini Material Recovery Facilities

This research explores the disruption of centralised waste facilities to accommodate a decentralised model, known as the mini-MRF, that is capable of extracting more value out of waste streams….

READ POST
WasteNet

Deep Learning: Unsupervised Domain Adaptation

The goal of this WasteNet series is to engineer a Deep Learning model that will focus on UDA for the instance segmentation task. As such, there are only two other approaches that are addressing this. …

READ POST