Illuminate Project

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Project Objectives

The concept of the ILLUMINATE project is to develop methods and processes for two main areas of the supply chain: collection of the waste streams and sorting of the waste, then develop automated systems that are able to effectively sort bulbs into different classes and remove foreign objects. This is essential for an economically viable process. The unit will be a multisensor system, combining machine-based recognition technique with sensors measuring e.g. weight, colour and/or shape, and being able to rapidly recognize the main types of lamps (brands) in the waste stream. Once the identification and separation has been achieved.

The concept of the ILLUMINATE project is to develop methods and processes for two main areas of the supply chain: collection of the waste streams and sorting of the waste, then develop automated systems that are able to effectively sort bulbs into different classes and remove foreign objects. This is essential for an economically viable process. The unit will be a multisensor system, combining machine-based recognition technique with sensors measuring e.g. weight, colour and/or shape, and being able to rapidly recognize the main types of lamps (brands) in the waste stream. Once the identification and separation has been achieved.

Operation

Current situation

Target achievement

Collection/transportation

Substantial fraction of lamps broken, contaminated with mercury, which may also leak to the environment via air or water

90% reduction of lamp breakage, mercury released from lamps is immobilized in collection container

Discharging and sorting at pre-processing site

Rough unloading which increases breakage. Manual time-consuming, sorting of lamps.

Simplified, automated unloading and sorting with a minimum of manual operation reduces process time 12-fold and minimizes exposure of staff to mercury

Pre-processing/shredding/crushing

All lamp types are at risk of mercury contamination

Mercury should only be in discharge lamp types, e.g. CFL’s.

Process information logging

Simple data generated via time-consuming, manual data in-feeding 

Complex and extensive process and waste data are generated automatically

Process control

Manual settings by experience. 

Information from sorting step fed into pre-processing steps for accurate settings

Process development

Process maintenance or investment decisions are taken based on emergency situations

Trends in waste flow, operation, and yield can be detected and used for well-motivated actions in time

Payment models/producer responsibility

Based on data from random analysis (manual operation)

Data on waste flow, manufacturer, processing time, etc are automatically generated in detail

FP7